By Robert Coopersmith, Director, Scientific Informatics, Hawkins Point (a Verista Company)
The cost of bringing a new prescription pharmaceutical to market is estimated to be a staggering $1-2 billion. This includes the actual R&D costs sunk into failed compounds, as well as the opportunity costs, in both time and money, of molecules that never get FDA approval. Over half of the expense is associated with clinical trials, yet compounds reaching Phase 1 trials have only about a 12% chance of eventual success. Therefore, culling prospective failures from the pipeline as early as possible, (preferably before entering clinical trials) can dramatically reduce the cost of development.
Those of us entering the Life Sciences industry from a scientific background have been inculcated since graduate school with the mantra “Don’t fall in love with your hypotheses.” Successful science depends on the dispassionate and objective attempt to disprove one’s brilliantly conceived theories, as emotionally difficult as that may be. In academic biomedical research, the costs of failing to heed this include perpetuation of unfounded ideas, wasted resources such as substantial funds from granting agencies that could have been diverted to more fruitful endeavors, and damage to the careers of investigators, graduate students, and postdocs. In Pharma and Biotech drug development the costs of over-attachment to an eventually doomed drug occur on a much larger scale; hundreds of scientists may be involved in a development program, and progression of a candidate too far down the pipeline can cost tens, if not hundreds, of millions of dollars.
There are both policy- and science-based strategies to help ensure that programs are halted when appropriate. For example, optimally, a compound will have to progress through a series of Yes/No Stage Gates at defined R&D pipeline milestones; there should be a rigorous review at each gate with broad involvement of scientific management stakeholders. There should also be an incentive structure in place such that there is no negative impact on a team if a program is terminated; this will promote objective assessment throughout the development process, minimizing potential “turf” issues between program teams. From a scientific standpoint, among other measures, a sound strategy is the implementation of technologies to provide early signals, both from an efficacy and a safety perspective, of how a molecule may fare in the clinic. Among others, these might include biomarker discovery strategies and predictive models using Real World Evidence (RWE). Additionally, the efficient capture, storage, sharing, and analysis of research data is essential to all the scientific decisions concerning a molecule’s progress through the pipeline.
Both the planning and implementation of the above measures involve a multiplicity of elements. The policy-based approaches require components of strategic analysis and planning, project management, change management, data governance, data management, business intelligence, and commercial factors. In addition, the scientific aspects also require elements of research informatics, research platforms, data science, and CMC. At Verista, our experienced team has expertise in all these areas. Whether your company is a start-up looking to establish these measures de novo, or an established company hoping to improve or add to existing processes, we can guide your company through analysis, planning, and implementation of strategies to reduce late-stage compound attrition.
Robert Coopersmith is a biopharmaceutical industry professional with deep expertise in drug discovery and development process, molecular oncology, personalized medicine, neurobiology (spanning cellular through molecular), knowledge management, bioinformatics/genomics/computational biology, and cell biology.