Agenda Automating Drug Development via AI and 3D Printing NLP in Drug Development Speaker Prof. Moe Elbadawi, Queen Mary University For details of our full Pharma and Life Science AI/ML Training Program and how to register, please click here.
Data inter-operability is a key enabler to accelerate life science workflows. Yet, many concrete hurdles exist. For example, organizations use different definitions for similar core concepts, requiring significant amounts of mappings across data sets even within a given company. The first objective of the Pharma General Ontology (PGO) project is to define a set of […]
GenAI shows promise in drug discovery, but cutting through the noise to understand where it’s truly making an impact can be difficult. This webinar will focus on how genAI is being applied in practical ways today, from designing novel molecules to predicting toxicity and extracting knowledge from complex datasets. Asha Mahesh from Johnson & […]
AI/ML is ubiquitous across the pharma industry, at least as a label. Do all AI/ML activities actually represent artificial intelligence? We will first frame AI and ML separately, and describe why we might want one or the other. With a definition in place, we will highlgiht examples of ML/AI applications across the entire drug discovery […]
In the preclinical development phase of drug discovery, timely access to relevant historical data can directly impact decision-making, regulatory timelines and study design. Yet, most pharmaceutical organizations still rely on scattered systems and manual workflows to extract insights from vast volumes of structured and unstructured study data. In this webinar, we present PRINCE—Bayer’s innovative […]
