DOMINIC COYLE
Blockbuster drugs coming off patent will knock a major hole in our export figures and tax revenues
PHARMACEUTICALS HAVE been a driving force for Ireland’s export success in recent years. Even through the darkest days of our financial collapse and recession, the sector, dominated by the large multinational players, continued to deliver export growth and a glimmer of hope of economic recovery.
However, the most recent trade figures point to a looming problem for the Government. Reporting a 9 per cent fall in exports in December, the Central Statistics Office was unusually frank and detailed in stating that “a substantial part of the decline in the value of exports was due to a high value product in the chemicals and related products sector coming off patent”.
The drug is Lipitor, Pfizer’s blockbuster cholesterol lowering therapy and the world’s best-selling drug in recent years, accounting for revenues of $10.7 billion in 2010. Pfizer’s Cork plant produces 100 per cent of the company’s global requirements for the active pharmaceutical ingredient in the drug and a significant portion of the finished tablets.
Coming off patent will knock a major hole in the future revenues Pfizer can expect to get from the drug as generic competition kicks in. As a rule, loss of patent protection can hit the value of sales by anything between 40 and 70 per cent over time – and not much time at that.
For Ireland, the concern in the December figures was that, for now, generic competition to Lipitor is limited. If that was enough to skew the export figures so dramatically, the worry is what damage future, more intense competition will do to our trade balance.
And Lipitor is just one of a number of key drugs in which Ireland has a commercial interest and which are coming off patent. Chris van Egeraat, a lecturer in economic geography at NUI Maynooth, says seven of the 10 largest-selling drugs worldwide which are losing patent protection are currently produced in Ireland. They include the best-selling drug worldwide in 2010 after Lipitor; Sanofi/Bristol Myers Squibb’s blood clotting treatment Plavix, with sales of $9.43 billion. It comes off patent in May.
Globally, it is estimated that as much as $100 billion in sales will be lost to drug companies between 2009 and 2014 as a result of drugs coming off patent. Expected pipeline delivery in terms of market revenue over the same time amounts to about $30 billion, Dr van Egeraat says.
While he doesn’t expect the loss of patents to lead to huge imminent job losses, it does highlight the ambition of the Government’s new Action Plan for Jobs, which has targeted the health and life sciences sector for significant growth in the coming years to help reach the Government’s 100,000 job target.
However, loss of market sales will clearly impact on trade figures and tax revenues. The Irish Pharmaceutical Healthcare Association (IPHA notes that the pharmaceuticals sector accounts for roughly half of all exports and is the largest contributor to corporation tax, accounting for roughly 50 per cent of the ˆ3.5 billion collected last year.
In employment terms, IPHA president and Pfizer country manager David Gallagher says that about 25,000 people are employed directly in the industry, with a roughly similar number working in related sectors. He notes that pharmaceuticals has been more resilient than other sectors of the economy during recent “economically challenging times”.
The message is pointed, especially at a time when the sector is locked in a dispute with the Government over access to market for its new drugs and the contribution it can make to savings in the health budget sought by the State.
David Gallagher noted recently that an increasing number of innovative medicines are currently not being reimbursed by the Department of Health, despite being approved by regulators and meeting health technology assessments.
He recently accused the department of acting in bad faith by refusing to approve drugs for reimbursement as provided for under the industry’s current pricing agreement with the Department, even though the industry had delivered savings of about ˆ540 million over the past five years, a figure he says equates to a 20 per cent cut.
Even before the latest row, the IPHA said the delay between approval and market access had jumped by over 50 per cent to 157 days in recent years, and only 64 per cent of drugs that received market authorisation in the EU between 2007 and 2009 were made available to patients here.
Matt Moran, director of Ibec group PharmaChem Ireland, said Government policy “needs to urgently recognise the very serious challenges facing the industry”.
“A number of blockbuster drugs are coming off patent and healthcare spending in Ireland has been cut by ˆ600 million in the last five years,” he said. “The future success of the sector must not be taken for granted.”
In a speech last year, Gallagher said further price concessions were “simply untenable”, citing preliminary 2011 figures pointing to a 5.2 per cent decline in the value of the Irish market. “There is a limit to the amount which can be taken out of a market without its effective operation and employment being jeopardised,” he said.
Ireland is not alone. The commercial prospects for big pharma were also thrown into sharp focus with a report on the UK’s pharmaceuticals price regulation scheme, which reported collective industry losses of ?142 million in 2009 despite rising sales.
For its part, the Department of Health needs to find cuts in its budget. In a recent report on pharma pricing, the Economic and Social Research Institute (ESRI said that drug costs account for about 17.5 per cent of public health expenditure in Ireland, up from 14 per cent in 2000.
In 2009, the ESRI says, spending per head of population in Ireland on pharmaceuticals was “amongst the highest in the OECD”.
It is understood the Department of Health is targeting a saving of about ˆ112 million from the drugs bill – either in terms of pricing and access for new medicines or pricing of generics.
The ESRI report recommended a number of approaches. These included pricing drugs on the basis of the lowest cost in a basket of European markets rather than the average, and more regular price updates to capture the impact of falling prices earlier.
The industry says that, despite the small physical size of the Irish market, such a move would be negative in two ways. First, Ireland is itself a component of pricing baskets in eight other larger EU markets. A “match the lowest” price here will inevitably further eat into prices in other more important markets.
Secondly, the industry points to Ireland’s importance as a base of operations for most of the main players in the sector. An increasingly adversarial approach with the State will only damage the prospects for future investment, they say, with one industry source saying the recent approach of the department to market access for new drugs was creating a very poor impression in a number of important boardrooms State-side.
The seriousness with which the pharmaceutical sector views the current price negotiations in Ireland – where eight of the top 10 global players have operations – is highlighted by the engagement of some of the industry’s leading figures with the Government.
The chief executive of one major global player has made a point of briefly visiting Ireland next week. The message in his first visit to the State will not be lost on ministers. The following week, leading executives from another top 10 drug manufacturers gather in Dublin for a meeting at which the attitude of the State to the sector is certain to figure.
On the Government’s side, there is concern too at any adverse impact on such a major employer and contributor to the exchequer. Taoiseach Enda Kenny has recently engaged directly in private meetings with top industry figures here to assure them of the Government’s support despite the ongoing budgetary squeeze.
For their part, the drug companies say that current pricing pressures are restricting innovations. Without adequate compensation, they say, companies simply will not be able to invest in new products given the costs involved and the risk of failure.
This isn’t unique to Ireland. Reporting annual results earlier this month, Bayer chief executive Marijn Dekkers expressed concern “about the side-effects” of health service reforms taking place around the world “because the money we earn from today’s medicines pays for the development of tomorrow’s medicines”.
Pointing to the ˆ2 billion research and development cost of Xarelto, a new drug developed with Johnson Johnson to prevent blood clotting, he said: “We need innovative pharmaceuticals more than ever, because so many known diseases still cannot be treated adequately, or at all, with medicines.”
But that’s part of the problem for the major pharmaceutical companies. Many of the easy treatment areas are now well catered for. A good portion of the drugs that do so are shortly coming off patent and are easily accessible to generic competition.
The opportunities of the future lie in increasingly niche conditions or very high risk areas such as oncology and, especially, neurology. Added to this is the move to biologics and the trend towards more personalised medicines.
The challenge is evident in the fact that, last year, the US drug regulator, the Food and Drug Administration, licensed just a handful of new pharmaceutical therapies. Getting this more select group of drugs to as many markets as possible is increasingly critical for big pharma.
The age of the blockbuster is fading, along with the fat profit margins it offered. That presents major issues for the sector. Over time, through consolidation and acquisition, they have grown into massive unwieldy entities with poorly directed research failing to deliver sufficient pipeline.
In recent years, much effort has been devoted to streamlining operations and increasing productivity, especially on the research side. Thousands of jobs have been shed worldwide, and greater emphasis placed on outsourcing much of the early-stage RD work.
A case in point is Elan’s prospective Alzheimer’s treatment bapineuzumab. Originally developed by the company in association with Wyeth, it is now controlled by Pfizer (which acquired Wyeth to fill a perceived weakness in its biopharmaceuticals operations and Johnson Johnson, which bought an 18.4 per cent stake in Elan in 2009 in a deal valued at $1 billion. Its interest was driven largely by the Irish company’s pipeline – particularly bapineuzumab which is seen as one of the more promising candidates to address a disease with limited treatment options at present and which reports critical Phase III trial data later this year.
The second focus is on developing new markets. But that presents its own problems, not least with business practices that have reflected poorly on the industry.
Several of the largest drug companies have been implicated in an ongoing legal action in Serbia in which a group of 10 doctors and drug company officials were charged with taking, or offering, more than ˆ500,000 in bribes to use specific products. While all deny guilt in this case, an examination of US Securities and Exchange Commission (SEC filings by the world’s top 10 drug companies has found that eight of them recently warned of potential costs related to charges of corruption in overseas markets.
Life is unlikely to get any easier for the sector over the coming two or three years. That raises the stakes in the ongoing price negotiations. The new accord was due to come into force yesterday and, as the leaked Commission assessment this week illustrated, pressure on the Government to deliver the necessary savings to ensure their budgetary projections is only likely to intensify.
LONDON, March 1 |
(Reuters - The global pharmaceutical industry is tightening its code of practice in a bid to stamp out bribery and corruption, particularly in emerging markets.LONDON, March 1
The International Federation of Pharmaceutical Manufacturers and Associations said on Thursday it had expanded and strengthened the code to ensure "the highest ethical and professional standards".
FREE GUIDES AND REPORTS FROM DIANOMIADVERTISEMENTBribes paid to foreign doctors and other state employees are shaping up as a major legal liability threat for Big Pharma, which has already forked out billions of dollars to settle mis-selling scandals in the United States.
Johnson & Johnson settled for $78 million with British and U.S. authorities last April, after disclosing payments to doctors in
Greece, Poland and Romania, while Pfizer reached an outline deal in a separate case late last year.
The new IFPMA code extends the rules covering drug company behaviour to also include interactions with medical institutions and patient organisations, as well as healthcare professionals, such as prescribing doctors.
It also makes clearer the dividing line between promotional aid and items of medical utility - which are allowed, and personal and cash gifts - which are not.
Permitted payments for entertainment are being curtailed, although they will still be allowed when interactions with drug firms are of a scientific or educational nature, including events at large medical meetings.
"The new code provides a framework for the industry to act with integrity and build trust," said IFPMA President and AstraZeneca CEO David Brennan. "This is not about doing the easy thing, but the right thing."
The Geneva-based organisation sees a particular role for its expanded code of practice in thinly regulated and smaller emerging markets, where national pharmaceutical organisations may have no presence.
But Tim Reed, director of Health Action International, an Amsterdam-based group that is critical of many industry practices, is not convinced the IFPMA has the teeth to make sure its edicts are implemented on the ground.
In the five years since the publication of the last code, the IFPMA has examined only four complaints against member companies - although more cases have been taken up by national organisations.
"There is a difference between intent and action," Reed said. "When you drill down to what is happening in developing countries, it is clear that it is just not applied. There is a real problem with enforcement because there is no punitive action as a result of transgression." (Editing by
Kate Kelland and
Jodie Ginsberg
More than 5,000 lawsuits have been initiated related to faulty hip replacements in the United States, but the frightening thing is that the flawed device came to market because of a regulatory loophole.
The Food and Drug Administration allows devices to come to market without testing on patients if the manufacturer can show there’s a "predicate," a similar device that was approved earlier.
But what if that predicate was pulled from the market when its maker realized it had flaws? Doesn’t matter.
A voluntary recall, not a recall by the FDA, allows the design to be picked up by other manufacturers and survive as a repeat offender. That means the new device maker can sail onto the market — with the wind of a bad product at its back.
Now, House Democrats have proposed a bill to deal with the loophole that allows these faulty designs a second life. It gives the FDA the power to reject devices that are based on flawed designs recalled by manufacturers. It’s a sensible response that places consumer safety first.
In addition to endangering consumers, the loophole undermines the FDA’s credibility. The agency’s safety designation should be above reproach.
Already, medical representatives say the bill is overkill, another regulation to burden manufacturers. But an FDA official who oversees medical devices says the change could make approvals easier, shortening the negotiations about questionable designs. And makers of the new device would have the opportunity to show how earlier errors had been corrected, or no longer relevant.
That’s fair for both seller and buyer. Consumers shouldn’t have to endure the pain and cost of replacing devices that have the same DNA as Brand X.
The European Commission
said it ended an antitrust probe into
GlaxoSmithKline Plc (GSK over possible collusion to keep cheaper copies of medicines off the market after a complaint against the company was withdrawn.
“The Commission examined whether there may have been violation of EU competition law by GlaxoSmithKline,” Antoine Colombani, a spokesman for the regulator, said in an e- mail. The case involving generic-drug producer Synthon BV concerned “possible anticompetitive agreements or concerted practices in order to delay or exclude generic competition,” he said. Colombani declined to elaborate on Synthon’s role in the probe.
The announcement comes a day after European Union regulators
dropped a similar probe into
AstraZeneca Plc (AZN , the U.K.’s second-biggest drugmaker, and
Takeda Pharmaceutical Co. (4502 ’s Nycomed unit over possible collusion to keep cheaper copies of medicines off the market. That case was brought to a halt because of a lack of evidence.
Doctors can still get free samples of medicines, though not football tickets or lunch for their spouses, under a revised code of conduct drafted by a global drug industry trade group.
The new rules clarify the differences between gifts, promotional aids and items such as anatomical models that can be used in medical practice, the
International Federation of Pharmaceutical Manufacturers & Associations said today in a statement. The federation’s member companies will be required to adopt the new guidelines and provide related training to their 1.3 million employees, the group said.
The code may help curb legal expenses related to marketing, particularly in the U.S., where
GlaxoSmithKline Plc (GSK last year agreed to pay $3 billion to resolve criminal and civil investigations and other matters.
Pfizer Inc. (PFE and
Eli Lilly & Co. (LLY each paid more than $1 billion to settle marketing allegations in 2009.
Novartis AG (NOVN and
AstraZeneca Plc (AZN are among drugmakers that in the past year have disclosed U.S. subpoenas seeking information on the selling of certain products.
“The new code provides a framework for the industry to act with integrity and build trust,” AstraZeneca Chief Executive Officer David Brennan, the federation’s president, said in the statement. “This is not about doing the easy thing, but the right thing.”
Free Samples
Free samples of medicines may be given to doctors who are authorized to prescribe them to patients, the federation said in the code. Companies should avoid extravagant venues for meetings, be transparent in promotional materials, and shouldn’t offer items for the personal benefit of a doctor or nurse, such as gift certificates or concert tickets, according to the guidelines.
“As a general rule, the hospitality provided must not exceed what participants would normally be prepared to pay for themselves,” the federation said in the code. “Companies should not pay any costs associated with individuals accompanying invited health-care professionals.”
The rules don’t address direct-to-consumer advertising, pricing or other trade terms for supplying wholesalers and other commercial customers, or promotion of medical devices, the federation said. Drugmakers that fund patient advocacy groups shouldn’t insist on being the sole sponsor of such an organization, and should outline in writing the nature of the financial support, according to the code.
To contact the reporter on this story: Kristen Hallam in London at
khallam@bloomberg.net
To contact the editor responsible for this story: Phil Serafino at
pserafino@bloomberg.net
A modified osteoporosis treatment drug might be able to tackle human malaria infections, according to new US research.
Based at the University of Illinois, a team spearheaded by Professor Eric Oldfield has discovered that this drug, in adapted form, can enter malaria-infected red blood cells and destroy the disease although, so far, only in mice.
Crucially, though, no significant side effects were recorded as far as the mice's health was concerned.
Modified Osteoporosis Drug
The modified osteoporosis drug draws on chemically-altered variants of zoledronate (marketed as Zometa and risedronate (marketed as Actonel . These, in their original forms, can't traverse the membrane that surrounds red blood cells but, with the addition of new features like an extended lipid structure, they're able to get through.
"We found that compounds that were really active had a very long hydrocarbon chain", Oldfield explained, in a statement. "These compounds can cross the cell membrane and work at very low concentrations."
Malaria Drug Treatments
According to the World Health Organization, it's possible that malaria infections claimed the lives of over one million victims in 2008, the majority of them located in Asia and Sub-Saharan Africa. The parasite that causes malaria is ever-changing and that means, in theory, Malaria drug treatment developers are caught in a constant catch-up game.
There's a constant stream of emergent malaria strains that no treatments presently in production can tackle and that's why, according to Oldfield: "it's important to find new drug targets because malaria drugs last only a few years, maybe 10 years, before you start to get resistance. The parasites mutate and then you lose your malaria drug."
Further details of this new malaria treatment research have been published by the Proceedings of the National Academy of Sciences.
Image copyright US Centers for Disease Control and Prevention
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Why Most Published Research Findings Are False
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John P. A. Ioannidis
Abstract Top
Summary
There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.
Citation: Ioannidis JPA (2005 Why Most Published Research Findings Are False. PLoS Med 2(8 : e124. doi:10.1371/journal.pmed.0020124
Published: August 30, 2005
Copyright: © 2005 John P. A. Ioannidis. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Competing interests: The author has declared that no competing interests exist.
Abbreviation: PPV, positive predictive value
John P. A. Ioannidis is in the Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece, and Institute for Clinical Research and Health Policy Studies, Department of Medicine, Tufts-New England Medical Center, Tufts University School of Medicine, Boston, Massachusetts, United States of America. E-mail: jioannid@cc.uoi.gr
Published research findings are sometimes refuted by subsequent evidence, with ensuing confusion and disappointment. Refutation and controversy is seen across the range of research designs, from clinical trials and traditional epidemiological studies [ 1–3] to the most modern molecular research [ 4, 5]. There is increasing concern that in modern research, false findings may be the majority or even the vast majority of published research claims [ 6–8]. However, this should not be surprising. It can be proven that most claimed research findings are false. Here I will examine the key factors that influence this problem and some corollaries thereof.
Modeling the Framework for False Positive Findings Top
Several methodologists have pointed out [ 9–11] that the high rate of nonreplication (lack of confirmation of research discoveries is a consequence of the convenient, yet ill-founded strategy of claiming conclusive research findings solely on the basis of a single study assessed by formal statistical significance, typically for a p -value less than 0.05. Research is not most appropriately represented and summarized by p -values, but, unfortunately, there is a widespread notion that medical research articles should be interpreted based only on p -values. Research findings are defined here as any relationship reaching formal statistical significance, e.g., effective interventions, informative predictors, risk factors, or associations. “Negative” research is also very useful. “Negative” is actually a misnomer, and the misinterpretation is widespread. However, here we will target relationships that investigators claim exist, rather than null findings.
It can be proven that most claimed research findings are false
As has been shown previously, the probability that a research finding is indeed true depends on the prior probability of it being true (before doing the study , the statistical power of the study, and the level of statistical significance [ 10, 11]. Consider a 2 ? 2 table in which research findings are compared against the gold standard of true relationships in a scientific field. In a research field both true and false hypotheses can be made about the presence of relationships. 1 Let R be the ratio of the number of “true relationships” to “no relationships” among those tested in the field. R is characteristic of the field and can vary a lot depending on whether the field targets highly likely relationships or searches for only one or a few true relationships among thousands and millions of hypotheses that may be postulated. Let us also consider, for computational simplicity, circumscribed fields where either there is only one true relationship (among many that can be hypothesized or the power is similar to find any of the several existing true relationships. The pre-study probability of a relationship being true is R /( R + 1 . The probability of a study finding a true relationship reflects the power 1 - ? (one minus the Type II error rate . The probability of claiming a relationship when none truly exists reflects the Type I error rate, ?. Assuming that c relationships are being probed in the field, the expected values of the 2 ? 2 table are given in Table 1. After a research finding has been claimed based on achieving formal statistical significance, the post-study probability that it is true is the positive predictive value, PPV. The PPV is also the complementary probability of what Wacholder et al. have called the false positive report probability [ 10]. According to the 2 ? 2 table, one gets PPV = (1 - ? R /( R - ?R + ? . A research finding is thus more likely true than false if (1 - ? R > ?. Since usually the vast majority of investigators depend on a = 0.05, this means that a research finding is more likely true than false if (1 - ? R > 0.05.
Table 1. Research Findings and True Relationships
doi:10.1371/journal.pmed.0020124.t001
What is less well appreciated is that bias and the extent of repeated independent testing by different teams of investigators around the globe may further distort this picture and may lead to even smaller probabilities of the research findings being indeed true. We will try to model these two factors in the context of similar 2 ? 2 tables.
Bias Top
First, let us define bias as the combination of various design, data, analysis, and presentation factors that tend to produce research findings when they should not be produced. Let u be the proportion of probed analyses that would not have been “research findings,” but nevertheless end up presented and reported as such, because of bias. Bias should not be confused with chance variability that causes some findings to be false by chance even though the study design, data, analysis, and presentation are perfect. Bias can entail manipulation in the analysis or reporting of findings. Selective or distorted reporting is a typical form of such bias. We may assume that u does not depend on whether a true relationship exists or not. This is not an unreasonable assumption, since typically it is impossible to know which relationships are indeed true. In the presence of bias ( Table 2 , one gets PPV = ([1 - ?] R + u ? R /( R + ? ? ? R + u ? u ? + u ? R , and PPV decreases with increasing u , unless 1 ? ? ? ?, i.e., 1 ? ? ? 0.05 for most situations. Thus, with increasing bias, the chances that a research finding is true diminish considerably. This is shown for different levels of power and for different pre-study odds in Figure 1. Conversely, true research findings may occasionally be annulled because of reverse bias. For example, with large measurement errors relationships are lost in noise [ 12], or investigators use data inefficiently or fail to notice statistically significant relationships, or there may be conflicts of interest that tend to “bury” significant findings [ 13]. There is no good large-scale empirical evidence on how frequently such reverse bias may occur across diverse research fields. However, it is probably fair to say that reverse bias is not as common. Moreover measurement errors and inefficient use of data are probably becoming less frequent problems, since measurement error has decreased with technological advances in the molecular era and investigators are becoming increasingly sophisticated about their data. Regardless, reverse bias may be modeled in the same way as bias above. Also reverse bias should not be confused with chance variability that may lead to missing a true relationship because of chance.
Figure 1. PPV (Probability That a Research Finding Is True as a Function of the Pre-Study Odds for Various Levels of Bias, u
Panels correspond to power of 0.20, 0.50, and 0.80.
doi:10.1371/journal.pmed.0020124.g001
Table 2. Research Findings and True Relationships in the Presence of Bias
doi:10.1371/journal.pmed.0020124.t002
Testing by Several Independent Teams Top
Several independent teams may be addressing the same sets of research questions. As research efforts are globalized, it is practically the rule that several research teams, often dozens of them, may probe the same or similar questions. Unfortunately, in some areas, the prevailing mentality until now has been to focus on isolated discoveries by single teams and interpret research experiments in isolation. An increasing number of questions have at least one study claiming a research finding, and this receives unilateral attention. The probability that at least one study, among several done on the same question, claims a statistically significant research finding is easy to estimate. For n independent studies of equal power, the 2 ? 2 table is shown in Table 3: PPV = R (1 ? ? n /( R + 1 ? [1 ? ?] n ? R ? n (not considering bias . With increasing number of independent studies, PPV tends to decrease, unless 1 - ?
< a, i.e., typically 1 ? ? < 0.05. This is shown for different levels of power and for different pre-study odds in Figure 2. For n studies of different power, the term ? n is replaced by the product of the terms ? i for i = 1 to n , but inferences are similar.
Figure 2. PPV (Probability That a Research Finding Is True as a Function of the Pre-Study Odds for Various Numbers of Conducted Studies, n
Panels correspond to power of 0.20, 0.50, and 0.80.
doi:10.1371/journal.pmed.0020124.g002
Table 3. Research Findings and True Relationships in the Presence of Multiple Studies
doi:10.1371/journal.pmed.0020124.t003
Corollaries Top
A practical example is shown in Box 1. Based on the above considerations, one may deduce several interesting corollaries about the probability that a research finding is indeed true.
Box 1. An Example: Science at Low Pre-Study Odds
Let us assume that a team of investigators performs a whole genome association study to test whether any of 100,000 gene polymorphisms are associated with susceptibility to schizophrenia. Based on what we know about the extent of heritability of the disease, it is reasonable to expect that probably around ten gene polymorphisms among those tested would be truly associated with schizophrenia, with relatively similar odds ratios around 1.3 for the ten or so polymorphisms and with a fairly similar power to identify any of them. Then R = 10/100,000 = 10?4, and the pre-study probability for any polymorphism to be associated with schizophrenia is also R /( R + 1 = 10?4. 1 Let us also suppose that the study has 60% power to find an association with an odds ratio of 1.3 at ? = 0.05. Then it can be estimated that if a statistically significant association is found with the p -value barely crossing the 0.05 threshold, the post-study probability that this is true increases about 12-fold compared with the pre-study probability, but it is still only 12 ? 10 ?4 .
Now let us suppose that the investigators manipulate their design, analyses, and reporting so as to make more relationships cross the p = 0.05 threshold even though this would not have been crossed with a perfectly adhered to design and analysis and with perfect comprehensive reporting of the results, strictly according to the original study plan. Such manipulation could be done, for example, with serendipitous inclusion or exclusion of certain patients or controls, post hoc subgroup analyses, investigation of genetic contrasts that were not originally specified, changes in the disease or control definitions, and various combinations of selective or distorted reporting of the results. Commercially available “data mining” packages actually are proud of their ability to yield statistically significant results through data dredging. In the presence of bias with u = 0.10, the post-study probability that a research finding is true is only 4.4 ? 10?4. Furthermore, even in the absence of any bias, when ten independent research teams perform similar experiments around the world, if one of them finds a formally statistically significant association, the probability that the research finding is true is only 1.5 ? 10?4, hardly any higher than the probability we had before any of this extensive research was undertaken!
Corollary 1: The smaller the studies conducted in a scientific field, the less likely the research findings are to be true. Small sample size means smaller power and, for all functions above, the PPV for a true research finding decreases as power decreases towards 1 ? ? = 0.05. Thus, other factors being equal, research findings are more likely true in scientific fields that undertake large studies, such as randomized controlled trials in cardiology (several thousand subjects randomized [ 14] than in scientific fields with small studies, such as most research of molecular predictors (sample sizes 100-fold smaller [ 15].
Corollary 2: The smaller the effect sizes in a scientific field, the less likely the research findings are to be true. Power is also related to the effect size. Thus research findings are more likely true in scientific fields with large effects, such as the impact of smoking on cancer or cardiovascular disease (relative risks 3–20 , than in scientific fields where postulated effects are small, such as genetic risk factors for multigenetic diseases (relative risks 1.1–1.5 [ 7]. Modern epidemiology is increasingly obliged to target smaller effect sizes [ 16]. Consequently, the proportion of true research findings is expected to decrease. In the same line of thinking, if the true effect sizes are very small in a scientific field, this field is likely to be plagued by almost ubiquitous false positive claims. For example, if the majority of true genetic or nutritional determinants of complex diseases confer relative risks less than 1.05, genetic or nutritional epidemiology would be largely utopian endeavors.
Corollary 3: The greater the number and the lesser the selection of tested relationships in a scientific field, the less likely the research findings are to be true. As shown above, the post-study probability that a finding is true (PPV depends a lot on the pre-study odds (R . Thus, research findings are more likely true in confirmatory designs, such as large phase III randomized controlled trials, or meta-analyses thereof, than in hypothesis-generating experiments. Fields considered highly informative and creative given the wealth of the assembled and tested information, such as microarrays and other high-throughput discovery-oriented research [ 4, 8, 17], should have extremely low PPV.
Corollary 4: The greater the flexibility in designs, definitions, outcomes, and analytical modes in a scientific field, the less likely the research findings are to be true. Flexibility increases the potential for transforming what would be “negative” results into “positive” results, i.e., bias, u . For several research designs, e.g., randomized controlled trials [ 18–20] or meta-analyses [ 21, 22], there have been efforts to standardize their conduct and reporting. Adherence to common standards is likely to increase the proportion of true findings. The same applies to outcomes. True findings may be more common when outcomes are unequivocal and universally agreed (e.g., death rather than when multifarious outcomes are devised (e.g., scales for schizophrenia outcomes [ 23]. Similarly, fields that use commonly agreed, stereotyped analytical methods (e.g., Kaplan-Meier plots and the log-rank test [ 24] may yield a larger proportion of true findings than fields where analytical methods are still under experimentation (e.g., artificial intelligence methods and only “best” results are reported. Regardless, even in the most stringent research designs, bias seems to be a major problem. For example, there is strong evidence that selective outcome reporting, with manipulation of the outcomes and analyses reported, is a common problem even for randomized trails [ 25]. Simply abolishing selective publication would not make this problem go away.
Corollary 5: The greater the financial and other interests and prejudices in a scientific field, the less likely the research findings are to be true. Conflicts of interest and prejudice may increase bias, u . Conflicts of interest are very common in biomedical research [ 26], and typically they are inadequately and sparsely reported [ 26, 27]. Prejudice may not necessarily have financial roots. Scientists in a given field may be prejudiced purely because of their belief in a scientific theory or commitment to their own findings. Many otherwise seemingly independent, university-based studies may be conducted for no other reason than to give physicians and researchers qualifications for promotion or tenure. Such nonfinancial conflicts may also lead to distorted reported results and interpretations. Prestigious investigators may suppress via the peer review process the appearance and dissemination of findings that refute their findings, thus condemning their field to perpetuate false dogma. Empirical evidence on expert opinion shows that it is extremely unreliable [ 28].
Corollary 6: The hotter a scientific field (with more scientific teams involved , the less likely the research findings are to be true. This seemingly paradoxical corollary follows because, as stated above, the PPV of isolated findings decreases when many teams of investigators are involved in the same field. This may explain why we occasionally see major excitement followed rapidly by severe disappointments in fields that draw wide attention. With many teams working on the same field and with massive experimental data being produced, timing is of the essence in beating competition. Thus, each team may prioritize on pursuing and disseminating its most impressive “positive” results. “Negative” results may become attractive for dissemination only if some other team has found a “positive” association on the same question. In that case, it may be attractive to refute a claim made in some prestigious journal. The term Proteus phenomenon has been coined to describe this phenomenon of rapidly alternating extreme research claims and extremely opposite refutations [ 29]. Empirical evidence suggests that this sequence of extreme opposites is very common in molecular genetics [ 29].
These corollaries consider each factor separately, but these factors often influence each other. For example, investigators working in fields where true effect sizes are perceived to be small may be more likely to perform large studies than investigators working in fields where true effect sizes are perceived to be large. Or prejudice may prevail in a hot scientific field, further undermining the predictive value of its research findings. Highly prejudiced stakeholders may even create a barrier that aborts efforts at obtaining and disseminating opposing results. Conversely, the fact that a field is hot or has strong invested interests may sometimes promote larger studies and improved standards of research, enhancing the predictive value of its research findings. Or massive discovery-oriented testing may result in such a large yield of significant relationships that investigators have enough to report and search further and thus refrain from data dredging and manipulation.
Most Research Findings Are False for Most Research Designs and for Most Fields Top
In the described framework, a PPV exceeding 50% is quite difficult to get. Table 4 provides the results of simulations using the formulas developed for the influence of power, ratio of true to non-true relationships, and bias, for various types of situations that may be characteristic of specific study designs and settings. A finding from a well-conducted, adequately powered randomized controlled trial starting with a 50% pre-study chance that the intervention is effective is eventually true about 85% of the time. A fairly similar performance is expected of a confirmatory meta-analysis of good-quality randomized trials: potential bias probably increases, but power and pre-test chances are higher compared to a single randomized trial. Conversely, a meta-analytic finding from inconclusive studies where pooling is used to “correct” the low power of single studies, is probably false if R ? 1:3. Research findings from underpowered, early-phase clinical trials would be true about one in four times, or even less frequently if bias is present. Epidemiological studies of an exploratory nature perform even worse, especially when underpowered, but even well-powered epidemiological studies may have only a one in five chance being true, if R = 1:10. Finally, in discovery-oriented research with massive testing, where tested relationships exceed true ones 1,000-fold (e.g., 30,000 genes tested, of which 30 may be the true culprits [ 30, 31], PPV for each claimed relationship is extremely low, even with considerable standardization of laboratory and statistical methods, outcomes, and reporting thereof to minimize bias.
Table 4. PPV of Research Findings for Various Combinations of Power (1 - ? , Ratio of True to Not-True Relationships (R , and Bias (u
doi:10.1371/journal.pmed.0020124.t004
Claimed Research Findings May Often Be Simply Accurate Measures of the Prevailing Bias Top
As shown, the majority of modern biomedical research is operating in areas with very low pre- and post-study probability for true findings. Let us suppose that in a research field there are no true findings at all to be discovered. History of science teaches us that scientific endeavor has often in the past wasted effort in fields with absolutely no yield of true scientific information, at least based on our current understanding. In such a “null field,” one would ideally expect all observed effect sizes to vary by chance around the null in the absence of bias. The extent that observed findings deviate from what is expected by chance alone would be simply a pure measure of the prevailing bias.
For example, let us suppose that no nutrients or dietary patterns are actually important determinants for the risk of developing a specific tumor. Let us also suppose that the scientific literature has examined 60 nutrients and claims all of them to be related to the risk of developing this tumor with relative risks in the range of 1.2 to 1.4 for the comparison of the upper to lower intake tertiles. Then the claimed effect sizes are simply measuring nothing else but the net bias that has been involved in the generation of this scientific literature. Claimed effect sizes are in fact the most accurate estimates of the net bias. It even follows that between “null fields,” the fields that claim stronger effects (often with accompanying claims of medical or public health importance are simply those that have sustained the worst biases.
For fields with very low PPV, the few true relationships would not distort this overall picture much. Even if a few relationships are true, the shape of the distribution of the observed effects would still yield a clear measure of the biases involved in the field. This concept totally reverses the way we view scientific results. Traditionally, investigators have viewed large and highly significant effects with excitement, as signs of important discoveries. Too large and too highly significant effects may actually be more likely to be signs of large bias in most fields of modern research. They should lead investigators to careful critical thinking about what might have gone wrong with their data, analyses, and results.
Of course, investigators working in any field are likely to resist accepting that the whole field in which they have spent their careers is a “null field.” However, other lines of evidence, or advances in technology and experimentation, may lead eventually to the dismantling of a scientific field. Obtaining measures of the net bias in one field may also be useful for obtaining insight into what might be the range of bias operating in other fields where similar analytical methods, technologies, and conflicts may be operating.
How Can We Improve the Situation? Top
Is it unavoidable that most research findings are false, or can we improve the situation? A major problem is that it is impossible to know with 100% certainty what the truth is in any research question. In this regard, the pure “gold” standard is unattainable. However, there are several approaches to improve the post-study probability.
Better powered evidence, e.g., large studies or low-bias meta-analyses, may help, as it comes closer to the unknown “gold” standard. However, large studies may still have biases and these should be acknowledged and avoided. Moreover, large-scale evidence is impossible to obtain for all of the millions and trillions of research questions posed in current research. Large-scale evidence should be targeted for research questions where the pre-study probability is already considerably high, so that a significant research finding will lead to a post-test probability that would be considered quite definitive. Large-scale evidence is also particularly indicated when it can test major concepts rather than narrow, specific questions. A negative finding can then refute not only a specific proposed claim, but a whole field or considerable portion thereof. Selecting the performance of large-scale studies based on narrow-minded criteria, such as the marketing promotion of a specific drug, is largely wasted research. 1 Moreover, one should be cautious that extremely large studies may be more likely to find a formally statistical significant difference for a trivial effect that is not really meaningfully different from the null [ 32–34].
Second, most research questions are addressed by many teams, and it is misleading to emphasize the statistically significant findings of any single team. What matters is the totality of the evidence. Diminishing bias through enhanced research standards and curtailing of prejudices may also help. However, this may require a change in scientific mentality that might be difficult to achieve. In some research designs, efforts may also be more successful with upfront registration of studies, e.g., randomized trials [ 35]. Registration would pose a challenge for hypothesis-generating research. Some kind of registration or networking of data collections or investigators within fields may be more feasible than registration of each and every hypothesis-generating experiment. Regardless, even if we do not see a great deal of progress with registration of studies in other fields, the principles of developing and adhering to a protocol could be more widely borrowed from randomized controlled trials.
Finally, instead of chasing statistical significance, we should improve our understanding of the range of R values—the pre-study odds—where research efforts operate [ 10]. Before running an experiment, investigators should consider what they believe the chances are that they are testing a true rather than a non-true relationship. Speculated high R values may sometimes then be ascertained. As described above, whenever ethically acceptable, large studies with minimal bias should be performed on research findings that are considered relatively established, to see how often they are indeed confirmed. I suspect several established “classics” will fail the test [ 36].
Nevertheless, most new discoveries will continue to stem from hypothesis-generating research with low or very low pre-study odds. We should then acknowledge that statistical significance testing in the report of a single study gives only a partial picture, without knowing how much testing has been done outside the report and in the relevant field at large. Despite a large statistical literature for multiple testing corrections [ 37], usually it is impossible to decipher how much data dredging by the reporting authors or other research teams has preceded a reported research finding. Even if determining this were feasible, this would not inform us about the pre-study odds. Thus, it is unavoidable that one should make approximate assumptions on how many relationships are expected to be true among those probed across the relevant research fields and research designs. The wider field may yield some guidance for estimating this probability for the isolated research project. Experiences from biases detected in other neighboring fields would also be useful to draw upon. Even though these assumptions would be considerably subjective, they would still be very useful in interpreting research claims and putting them in context.
References Top
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- Lawlor DA, Davey Smith G, Kundu D, Bruckdorfer KR, Ebrahim S (2004 Those confounded vitamins: What can we learn from the differences between observational versus randomised trial evidence? Lancet 363: 1724–1727. Find this article online
- Vandenbroucke JP (2004 When are observational studies as credible as randomised trials? Lancet 363: 1728–1731. Find this article online
- Michiels S, Koscielny S, Hill C (2005 Prediction of cancer outcome with microarrays: A multiple random validation strategy. Lancet 365: 488–492. Find this article online
- Ioannidis JPA, Ntzani EE, Trikalinos TA, Contopoulos-Ioannidis DG (2001 Replication validity of genetic association studies. Nat Genet 29: 306–309. Find this article online
- Colhoun HM, McKeigue PM, Davey Smith G (2003 Problems of reporting genetic associations with complex outcomes. Lancet 361: 865–872. Find this article online
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- Risch NJ (2000 Searching for genetic determinants in the new millennium. Nature 405: 847–856. Find this article online
- Kelsey JL, Whittemore AS, Evans AS, Thompson WD (1996 Methods in observational epidemiology, 2nd ed. New York: Oxford U Press. 432 p.
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- Moher D, Schulz KF, Altman DG (2001 The CONSORT statement: Revised recommendations for improving the quality of reports of parallel-group randomised trials. Lancet 357: 1191–1194. Find this article online
- Ioannidis JP, Evans SJ, Gotzsche PC, O'Neill RT, Altman DG, et al. (2004 Better reporting of harms in randomized trials: An extension of the CONSORT statement. Ann Intern Med 141: 781–788. Find this article online
- International Conference on Harmonisation E9 Expert Working Group (1999 ICH Harmonised Tripartite Guideline. Statistical principles for clinical trials. Stat Med 18: 1905–1942. Find this article online
- Moher D, Cook DJ, Eastwood S, Olkin I, Rennie D, et al. (1999 Improving the quality of reports of meta-analyses of randomised controlled trials: The QUOROM statement. Quality of Reporting of Meta-analyses. Lancet 354: 1896–1900. Find this article online
- Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, et al. (2000 Meta-analysis of observational studies in epidemiology: A proposal for reporting. Meta-analysis of Observational Studies in Epidemiology (MOOSE group. JAMA 283: 2008–2012. Find this article online
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- Altman DG, Goodman SN (1994 Transfer of technology from statistical journals to the biomedical literature. Past trends and future predictions. JAMA 272: 129–132. Find this article online
- Chan AW, Hrobjartsson A, Haahr MT, Gotzsche PC, Altman DG (2004 Empirical evidence for selective reporting of outcomes in randomized trials: Comparison of protocols to published articles. JAMA 291: 2457–2465. Find this article online
- Krimsky S, Rothenberg LS, Stott P, Kyle G (1998 Scientific journals and their authors' financial interests: A pilot study. Psychother Psychosom 67: 194–201. Find this article online
- Papanikolaou GN, Baltogianni MS, Contopoulos-Ioannidis DG, Haidich AB, Giannakakis IA, et al. (2001 Reporting of conflicts of interest in guidelines of preventive and therapeutic interventions. BMC Med Res Methodol 1: 3. Find this article online
- Antman EM, Lau J, Kupelnick B, Mosteller F, Chalmers TC (1992 A comparison of results of meta-analyses of randomized control trials and recommendations of clinical experts. Treatments for myocardial infarction. JAMA 268: 240–248. Find this article online
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- Ntzani EE, Ioannidis JP (2003 Predictive ability of DNA microarrays for cancer outcomes and correlates: An empirical assessment. Lancet 362: 1439–1444. Find this article online
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- Ioannidis JPA (2005 Contradicted and initially stronger effects in highly cited clinical research. JAMA 294: 218–228. Find this article online
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Permanente
Industria Farmaceutica
01/02/2012
Sobre nosso cliente
Company that has been consolidated in Brazil and is dedicated to developing manufacturing and marketing a product line that contribute to people's heath and well being.
Oferta:
Manage the sales/technical area, approve the finished product. Reporting to general director in Brazil.
Scope:
* Manage the Quality Management System of the company.
* Being a technical responsible for the company to ANVISA and other regulators.
* Be formal responsible for the approval of the finished product prior to release for sale.
* Represent the direction of third-party audits, as well as inspections by regulatory bodies and government authorities
* Be responsible for ensuring that customer complaints and nonconformities are treated in a timely manner in accordance with the policies of the organization
* Coordinate internal audits and self-inspections for GMP
* Run meetings to critically review the quality system with the board
* Manage the quality indicators in conjunction with other areas of the company
* Implement the policies established for the quality area in the form of standard procedures and work instructions
* Perform communication to regulators in case of need for product recall or any other warnings that may be required
* Guide, evaluate and motivate the team of his/her responsibility
* Train new leaders
* Approve documents for the quality system
* Actively contribute to maintain approved and within the valid period the operating licenses, product registrations and certificates of products and quality management system, including certification for Good Manufacturing Practices
* Develop strategic planning for Quality area in conjunction with the Board
Perfil desejado
- Requirement:
* Graduated in Pharmacy
* ISO 13485 Standard
* RDC 59/00
* Quality tools (PDCA, CEP, Pareto, Cause-Effect Diagram, Brainstorming, etc
* Good Manufacturing Practices
* Fluent English
* Leadership, Organization, Critical View, Initiative and Concentration
Referencia : GRFL104371
Seu curriculo sera analisado por Rafael Souza
In the neverending saga that is the Greek exchange offer we have a new and very important player: the head of the Greek debt management agency, Petros Christodoulou, who is now actively threatening any Greek hold out hedge funds against doing what is in their LPs' best interests (suing Greece and the EU and holding out for par recoveries - as
discussed here , by using not only the now trite and idiotic Mutual Assured Destruction clause which only those stuck in 2008 believe is remotely credible, but by advising hedge funds (which are actively forming ad hoc hold out committees as we speak,
just as we predicted 6 weeks ago that "there is just no money for holdouts...We are prepared for legal challenges but the risk here is that people are trying to be too smart." Oh, so now if one does what is in their interest, and dare hold out against collectivist fascist interests, they are "trying to be smart." We wonder if Mr. Christodoulou learned such brute force negotiating tactics at one of his former employers: JP Morgan or Goldman That's right - as we wrote
over two years ago, the man who is now negotiating for Greece's and Europe's life (because a failed PSI will not only trigger CDS, more importantly it will result in an
out of control default of Greece and likely its exist from the Euro and the Eurozone - two things that Germany would be delighted to see is a former employee of the two companies that just so happens are the co-chairmen of the US Treasury Borriwng Advisory Committee, or as we have also called it before, "
The Supercommittee That Really Runs America." Is the pattern finally emerging?
Mr. Christodoulou declined to comment on whether the clause would be activated but he did underline that the consequences of a failed deal are dire not just for Greece but for bondholders too.
The alternative, he said, “is too dire to contemplate.” He added that if this deal failed, the next offer bond holders would get would be far inferior, lacking the incentives that the current offer has.
Mr. Christodoulou said that it was too early to get a sense of what the participation rate would be but that he said he was confident that at the end of the day enough investors would agree to the deal to reach the target.
“We are targetting near universal participation,” he said. “We have spent a lot of time on this — now we are ready to implement it.
Also as said here countless times before, the hedge funds certainly have the upper hand in the standoff with Greece, if only they successfully collectivize and form a hold out stake. Guess what: that's precisely what they are doing, using Bingham McCutchen (if any readers have a Greek bond stashed somewhere, whether it is Greek or UK-law, and wish to prevent this travesty from happening, reach out to Bingham and join the hold out group .
Nevertheless numerous hedge funds have been accumulating a range of Greek bonds that are governed by foreign law in the hopes of of making a legal challenge. These securities range from bonds issued by Greece’s near bankrupt railway firm to so-called pharma bonds — bonds issued by the Greek government and paid to cash-starved Greek pharmaceutical companies in place of cash
Law firms like Bingham McCutchen have been soliciting hedge funds, asking that they form a consortium to challenge Greece by accumulating enough of these types of bonds so that they might be able to block the deal and perhaps receive near full payment from the Greek government.
The rationale being that Greece would rather pay off these investors as opposed to having to fight them in court.
Needless to say, the TBAC crony is not happy at the prospect of an out of control default collapse of the system unless the hedge fund hold outs aren't bribed to comply.
Mr. Christodoulou sees little chance of this happening.
“We feel we need to honor the long term investors who will participate in the deal,” he said. “It is not in anyone’s interest to see them take a 70 percent haircut while others get par.”
Uh sorry Pet, it's not about what seems fair to your crony accomplices. It's what makes the most money. And the best strategy right now is for hedge funds to build up pair trades (buy CDS and bonds going into the PSI and just say no, knowing very well that they have all the power in the world if more than 25% of hedge funds announce they refuse to participate in the coercive PSI.
Just as we have been saying for months.
And incidentally, here is a modest suggestion for Germany: if you want to hate someone, hate Goldman Sachs. After all, Goldman is the firm that spawned not only Mario Draghi who as we wrote yesterday is
now the most hated man in Germany, but also this Greek pawn whose only job now is to do everything in his power to keep Greece part of the Union - something that well over 60% of Germans do not want. And as a reminder, it was also
Goldman who allowed Greece to reach to its catastrophic debt load in the first place by coming up with clever ways to disguise its debt. Yup: if there is anyone who can play not both, but all three side of the game (including be the referee it's Goldman.
NATIONAL CONFERENCE ON
Current Trends in Medicinal, Aromatic plants and Plant Products
17th & 18th March 2012
Organized by
Osmania University, Hyderabad
OSMANIA UNIVERSITY- A BRIEF PROFILE :
Osmania university established in the year 1918, is the seventh oldest university in the country, third oldest in the South India and oldest in the sate of Andhra Pradesh. It was founded by His exalted Highness Mir Osman Ali Khan, the Seventh Nizam of Hyderabad State. It was the first University to impart higher education through Urdu as the medium of instruction. It is the largest affiliating university in Asia with close to 800 affiliated colleges spread over 3 districts of Telangana (Hyderabad , Ranga Reddy and Medak providing academic and research facilities for nearly five lakhs students. It was accredited with a ‘FIVE STAR’ rating by the NAAC in the year 2001 and reaccredited with the highest grade ‘A’ in 2008. It has been ranked 7th among
Botany
DEPARTMENT, OSMANIA UNIVERSITY :
The department of
Botany
, Osmania University is one of the oldest and pioneering department in the country with decades of academic contributions of excellence. The department has excellent infrastructural facilities and is carrying out research in cutting edge areas of pant sciences. The department has received grants from several national funding agencies like UGC in the form of SAP & COSIST,
CSIR
,
DBT
, DST, MoENF and APNL. DST identified the department under FIST programme.
The department is offering following specializations of contemporary relevance at
M.Sc
., level:
1. Applied Mycology and Molecular Plant pathology
2. Applied Physiology and
molecular biology
3. Biodiversity of Angiosperms, Phytochemistry and Biodiversity of Medicinal Plants.
4. Cytogenetics, Genetics and Molecular Genetics.
5. Applied Palynology and Palaeophytology.
ABOUT THE CONFERENCE :
Medicinal and Aromatic Plants have been used in different ways and methods in overcoming various health problems. Phytochemicals derived from medicinal Plants are been used in different systems of Medicine like Aurveda, Siddha, Unani, Homeopathy, Folklore and Allopathy. Majority of the Drugs used in Allopathy are derived from Medicinal Plants. Many of the Pharmaceutical and Agrochemical Industries are currently engaged actively in Research and Development of Eco-Friendly,organisms, Phytochemicals, and plant products like biofertilizers,biopesticides nutraceuticals,and dietary suppliments. Nearly 70-80 % of Population of Developing Countries are relining on Products which are of plant origin. This trend indicates the demanding position of Medicinal and Aromatic plants in the present market. Therefore this Conference reviews, discuseses,deliberate and share their Research experience for the benefit of students, teachers and researchers and comman man.
TECHNICAL PROGRAMME :
Theme of the Seminar will Review, Discuss and Deliberate on the following areas.
1. BIODERVISITY AND CONSERVATION OF MEDICINAL PLANTS
2. PHYTOCHEMISTRY,SECONDARY METABOLITES AND NATURAL PRODUCTS
3. CULTIVATION, MICROPROPAGATION AND
Biotechnology
OF MEDICINAL PLANTS
4. PHARMACOLOGY, PHARMOCOGNOSY AND ETHANOBOTANY
5. HERBAL PRODUCTS, EFFECT OF BOTANICALS ON MICROBES AND INSECTS
6. MEDICINAL PLANTS AND MICROBIAL INTERACTIONS
SUBMISSION OF ABSTRACTS :
The official language of the conference will be English. There will be Oral and Poster presentations. Oral presentation will be by invitations through respective technical session, Conveners. Contributed papers will be presented as posters. Abstracts of both invited and contributed papers will be printed and distributed to registered participants. Abstracts should be electronically typed on A4 size papers with 3cm margins on all sides, should not exceeded 300 words. Those interested to participate in the conference are requested to fill in the enclosed registration form and send it on or before 7th March, 2012
REGISTRATION FEES :
For participants : Rs 600. For students:300
PosterSize : 4ft×3ft
Please send with registration fees and abstract on or before 7th March2012 Positively to following address
Prof. G. Bagyanarayana
Convener
Department of
Botany
, Department of
Botany
Osmania university , Hyderabad-500007
Email: gbagyan@gmail.com
Prof. S. Gangadhar Rao
Organizing secretary
Osmania university, Hyderabad 500007
Email:
gangadharrao53@gmail.com
Deadline : 07.03.12
World Horse Welfare vets given go-ahead to use contraceptive injection on mares after Devon population explosion
A pioneering project to put Dartmoor's wild ponies on the pill is to begin in Devon later this year.
Concerns has been growing for several years about overbreeding among the semi-feral animals, high numbers of which have ended up in horse sanctuaries or slaughtered and the meat sold overseas as their market value has plummeted.
The recession has further affected sales of the ponies, with less people prepared to take on and train up a half-wild animal, despite their temperaments and intelligence making them ideal as children's riding ponies.
Now vets working for World Horse Welfare have been given the go-ahead to bring in injection from Australia to control the numbers of foals being born on the moor.
WHW veterinary consultant Keith Meldrum has been working closely with the Dartmoor Hill Pony Association (DHPA and the pharmaceutical company Pfizer on proposed plans to provide a group of 20 mares with a contraceptive injection.
"A project of this kind has never been carried out before in the UK and I am delighted to be a part of it," he said. "We are hoping that, if successful, this could become a long-term solution to the issue of overbreeding within Britain's semi-feral horse and pony populations."
Meldrum said the treatment was not as invasive as sterilising the mares.
"We feel that this method of control is advantageous as the mares can come back into foal after the treatment; its simply means there is simply a reduction in foal production for the duration of the project. We are close to starting the initial injections now that we have the [drug] in our possession and after the Veterinary Medicines Directorate gave us the go ahead for batches to be imported from Australia into the UK."
There are thought to be less than 1,000 of the ponies left on the moor, down from an estimated 25,000 in the 1930s. In late spring a team led by Meldrum plan to round up ponies into a holding area where they will be micro-chipped and marked in a way in which they are identifiable at a distance. They will then be given an injection, and four weeks later given a second dose.
After a six-month period the mares will be blood-tested to see if their oestrus levels have been suppressed owing to the injection. If the mares respond positively after the initial six months, then they will receive a further does which will last until spring 2013.
The secretary of the DHPA, Charlotte Faulkner said: 'The adult pony numbers on the moor need to be maintained at its present number for the benefit of Dartmoor, but the number of foals need to be reduced as there is no market for them at the moment.
"Controlling the production of unwanted foals will ensure the ponies' welfare. We are optimistic that this project will help us to ensure the future of ponies on Dartmoor, grazing to keep it as we know and love it for generations to come, creating the habitat for its wonderful birds, plants and animals to be conserved."
The project is being sponsored by Friends of the Dartmoor Hill Pony.
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