Mathematical Approaches for Predicting Risks Early-On in Drug R&D
Abstract
Published in Pharma Tech Outlook Magazine
Discovering a new drug or therapeutic candidate, going through regulatory approval, and bringing it to market is complicated and time-consuming. Developing a therapeutic requires an understanding of human biology, underlying causes of diseases, the interactions between drugs and the body, and several other factors. Moreover, the attrition rates are often high towards the later stages of the R&D pipeline as many promising candidates prove ineffective or toxic. What makes R&D projects even more sensitive is the amount of money and effort invested along with the crucial responsibility of health safety and compliance to medical guidelines. Predicting the complexities or risks is essential to eliminating the failures earlier and accelerating the winners into the clinic.
Applied BioMath offers biosimulation services and software to biotech and pharmaceutical companies, assisting them throughout the pipeline to help understand such complexities and identify risks early on.