Early this year, we shared an outlook giving an overview of the role of Artificial Intelligence in Drug Discovery. Through our conversations with several global pharma and biotechs, we realized that, while the enthusiasm around the potential of AI is high, a shadow of skepticism looms over. A common theme in our dialogs was on explaining the advantages of AI-based interventions over the traditional methods and what to expect out of AI-based platforms.
To help build a deeper perspective on AI intervention’s capabilities and the advantages, we are pleased to share an AI toolkit for early-stage drug discovery. The document outlines the small molecule/chemistry-oriented applications of AI and dissects the key parameters necessary for the success of an AI-driven approach. Moreover, we highlight relevant case studies to exemplify AI intervention’s advantages with respect to efficiency, cost, and time. Finally, we define the key parameters required to assess any AI platforms to suit one’s specific needs.
With 2020 marking the entry of the first AI-designed molecule in clinical trials, AI is poised to play an integral role in driving drug discovery in the coming decade. However, with 250+ AI-drug discovery start-ups flocking the space, it is necessary to ‘clear the noise’ and identify robust and appropriate platforms.
With our in-depth understanding of AI-Drug Discovery space, we would be delighted to further share our insights and catalyze your AI-Drug Discovery focused strategies.
Please download the presentation here – AI toolkit for early-stage drug discovery. We look forward to your feedback and would appreciate any queries/comments from your side.