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Blog Sax Risk Based
The incredibly high failure rates seen in clinical trials has pushed biopharmaceutical companies to aggressively manage the time and cost of these initiatives as a way to reduce their risk. Such efforts can deliver incremental savings on trial design, but too often these short-term gains increase the risk of long term losses. 

When clinical trial project teams face relentless pressure to cut costs and shorten time frames, it pulls their focus away from the long term goals of identifying the most promising drug candidates and delivering them to market. If they are being judged on how much they spend on every trial, they can’t make the best decisions for the long term success of a drug. Cutting overhead for example, may achieve short term savings goals, but it lessens their ability to gather the necessary data to validate a drugs performance. 

That’s not to say that biopharma should abandon efforts to gain efficiencies in drug trials. But before they make these choices, they must seek out the balance between time, cost, risk and ultimate value. 

They can do that by incorporating Net Present Value goals into every decision-making step. 

Whether you are considering strategies to cut time and expense, or determining the necessary sample size to de-risk failure in a Phase III trial, these are all value related decisions. To come to the right answer, stakeholders need to develop a system through which they are willing to weigh short term benefits against long term risk. 

These aren’t just decisions made in the isolation research and data analysis. Value based decision making informs choices by considering external data around commercial strategies, target populations, and the regulatory and payer environment in which the drug will exist. Through this clinical commercial convergence, stakeholders can make more informed choices. 

For example, if a new treatment targets a high risk high reward environment, where there are significant benefits to be gained from being ‘first to market,’ decision makers can prioritize speed over incremental cost; whereas if a drug targets a high risk but small population with a high price solution that has few competitors, going slower to better manage risks may be the better option. 

We can only make logical decisions when we take a holistic view of the data, and consider the broader ramifications of short term decisions. As long as you keep the end game in mind, and judge the value of any deviation in terms of whether it increases or decrease your probability of success, the long term goals will not be sacrificed.