In drug development, there is an inherent amount of uncertainty, which translates into risk. Uncertainty is caused by the organic nature of raw materials, making it impossible to predict how an Active Pharmaceutical Ingredient (API) will behave, how much yield can be achieved and how effective it will be, even for molecules having an otherwise perfect profile. A lack of efficacy can, for example, be the consequence of the wrong choice of target, the use of models that are not predictive for human disease, or failure of the molecule to engage the target in the clinical situation. Risks can come from an inability to characterize the right compound, the lack of suitable bioassays, an inability to generate the correct reagents or toxicity in the molecules.
Adding to this uncertainty are increasing pressures due to rising research and development (R&D) costs, expiring patents, increasing competition and regulatory requirements eroding profit margins.
In fact, developing a new prescription medicine that gains marketing approval is estimated to cost drug makers $2.6 billion according to a recent study by Tufts Center for the Study of Drug Development and published in the Journal of Health Economics. And, new drug discovery projects can take more than 12 years before they are commercialized.
As we’ve seen recently because of the pandemic, unforeseen factors can also impact risk, such as disrupted supply chains, plant shutdowns or reduced FDA review of non-COVID-related drug candidates.
A key area where risk can be minimized however, is in the R&D phase where APIs are created and Kilo-lab production takes place. An interesting line of thinking was addressed in an article in NCBI, which stated that, “in contrast to widespread scientific practice, experiments should be designed and executed to clearly demonstrate that the initial hypothesis is wrong—so called No-Go experiments.” The thinking is that failing in the earliest stages is less costly and resource-intensive than waiting until the project enters GMP manufacturing to fail.
Despite this “No-Go experiments” philosophy, there are many steps that can be taken to not only set up a project for success in the earliest stages, but to ensure that success continues beyond those stages and throughout the project’s lifecycle.
Managing risk in API R&D requires picking the right CDMO for the job, one that can carefully vet suppliers, implement the most robust methods and testing processes and that acutely understands your project and leverages its own experience and insights to ensure the best outcomes.
Consider the following five best practices to ensure success in R&D:
While drug development can be filled with risk that cannot be controlled, there are many ways that risk can be reduced in R&D. Strategically managing this risk at the earliest stages can help to save costs and valuable resources, as well as offer greater chances for success across the drug development journey.
For more insights on risk management in drug development, read What Should You Look for in a Consultant to Manage Your API Project?; Incomplete Documentation Can Make or Break Projects in API Manufacturing; or The Top 5 Reasons API Projects Fall Behind Schedule.