Biopharmaceutical Informatics: A Strategic Vision for Improved Translation of Biologic Drug Discoveries into Drug Products

Research scientists discover several promis­ing novel drug candidates every year, but only a few of these newly discovered compounds reach the clinic after several years. The current rate of translating drug discoveries into medicines is approximately 11%. A major portion of the developmental costs of new drugs is incurred during clinical trials, whose outcomes depend on the choices made during the selection (design) of the drug molecule, formulation, manufacturing, dosing, clinical trial design and patient population selection. The development projects that yield drug products, successfully, must recover costs for their development and those of the discontinued ones. This leads to high prices for the innovative drug products. The low translation rates and high development costs make drug discovery and commercialization a risky affair and point to inefficiencies in drug discovery, development and testing. While biological activ­ity is justifiably the focus during the discovery of biopharmaceutical candidates, the macromolecular sequence–structural properties of these candidates can also inform us about challenges in biologic drug development. These include cell line expression levels, purification column behavior, potential physicochemical degradation routes such as aggregation and chemical degradation hotspots, interactions with extractables and leachables, behaviors of highly concentrated solutions, immunoge­nicity, pharmacokinetics/dynamics, and so on. Such insights, when they come via computation at early stages of lead candidate design or selection, can significantly improve efficiency of biologics drug dis­covery and development.

In this talk, we intend to present our strategic vision for Biopharmaceutical Informatics. Biopharmaceutical Informatics combines information technology (database creation, curation and analytics) with computational biophysics (molecular modeling, simulations and structural bioinformatics) to help understand challenges faced during drug product development. For example, Biopharmaceutical Informatics can help selection of biologic drug candidates with favorable biophysical attributes at the early stages of product development. We have been building in silico tools that can rapidly identify biologic drug candidates with product development issues at early stages and suggest sequence optimizations for lead candidate(s) in a project. Early implementation of such predictive tools can shorten project timelines, save resources and avoid lengthy detours when unanticipated challenges are encountered later during product development. Potential applications of Biopharmaceutical Informatics at the later stages include improvements in cell-line productivity, drug substance purification yields, design of novel formulation excipients and assessing the impact of sequence variations on drug product quality.