How Big Pharma Might Get Its R&D Act Together
Try as they might, the scientific sleuths working for big drugmakers and aspiring biotechs have, generally, had a tough time in recent years developing a large cache of new medications. Certainly, there have been successes, but the industry continues to lament the challenges in filling its pipeline.
Meanwhile, there are complaints and concerns about the ensuing costs involved. So what might be the best approach – targeting diseases or mechanisms of action? Drug discovery is not an all-or-nothing pursuit, but which might provide a better outcome? Frank Sams-Dodd, chief scientific advisor to the Aslepios Bioresearch venture capital firm, co-founder of the Willingsford device maker and a former head of psychopharmacology at Boehringer Ingelheim has this to say…
For the past 20 years the pharmaceutical industry has invested billions of dollars into drug discovery and development. However, in spite of these investments, the industry has not been able to develop sufficient numbers of new drugs to replace existing drugs coming off patent and has therefore not been able to maintain its profitability. The result has over the past 5-7 years been increasing lay-offs, site closures and program terminations.
So, the key question is: what is the reason for this productivity failure? There have been many explanations, but a consistent observation is that the majority of new drugs fail during development due to lack of efficacy. This in turn indicates that it is how the industry conducts the drug discovery process that is the fundamental cause of the problem.
For most diseases, we do not understand the cause of the disease, we do not understand how the disease process affects the body and we do not understand how the majority of the effective drugs on the market interfere with the disease process or the symptoms to exert their therapeutic effects. A good example of the difficulty in developing new drugs is the current crisis with antibiotic resistant bacteria – we understand the cause of an infection (we can look at it in a microscope), but in spite of the fact that we have full disease insight we cannot develop an effective treatment.
The consequence of this is that the development of new treatments essentially is a question of how many new mechanisms, i.e. components in the body that a drug affects, or combinations of mechanisms that we can test for therapeutic efficacy in a particular disease – the more mechanisms the higher the probability of finding a treatment. It is not known how many possible ways of affecting the body there exist, but we do know that new biological mechanisms and complex interactions between different systems in the body are constantly discovered, so it is safe to assume that there is a very large number and that it includes many that we have not yet discovered.
Drug discovery can essentially be conducted using two different approaches: 1) a disease-based approach, where drugs are screened directly in a disease model for their ability to reduce the disease process or symptoms; and 2) a target-based approach, where the researcher first selects the mechanism that the drug should affect, next develops a drug with these properties and finally tests the drug in a disease model (often the same model as used for the disease-based approach) to demonstrate that the target-selective drug has therapeutic effects.
The advantage of the disease-based approach is that we do not need to understand how the drug works – the biology will show us whether the drug has the desired effect and this is enough. In contrast, the target-based approach requires that we select the mechanism whereby to treat the disease, which means that this approach is limited by how well we understand the disease and the biology of the body. The disadvantage of the disease-based approach is that it is time consuming to screen large numbers of drugs in complex disease models, whereas for the target-based approach thousands of drugs can be screened every week for selectivity against the target before final validation of therapeutic efficacy in a disease model.
To read the remainder of this article, go to Pharmalot.
Ed Silverman, a contributing editor of YCharts, is the founder and editor of Pharmalot. He previously reported on the pharmaceutical industry and other business topics for the Star-Ledger of New Jersey, New York Newsday and Investor’s Business Daily.
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