Use Cases for Artificial Intelligence and Machine Learning in Early-stage Life SciencesWhite paper
In every generation, certain technological advancements in healthcare have emerged that have “changed everything.” For example, the discovery of penicillin in the 1940s revolutionized medicine, transforming what was once a potentially deadly strep throat into a trivial infection. We now find ourselves at the dawn of another paradigm-shifting event: the rise of artificial intelligence (AI) and machine learning (ML) in medicine.
Among the various domains AI is set to revolutionize, none will be more profoundly affected than the life sciences in the drug discovery and development areas. The life sciences industry presents an array of use cases for AI and ML, ranging from accelerating research and development to optimizing clinical trials and improving patient outcomes. In this paper, we will explore ten use cases of AI and ML in research and development within the life sciences industry.
Steven Labkoff is one of the leading clinician-informaticians in the US today with nearly 30 years of experience in the life sciences and healthcare sector. Trained in medical informatics, cardiology, and internal medicine (Harvard, MIT, University of New Jersey, and University of Pittsburgh), Steve has deep expertise in generating, managing, and analyzing data to accelerate drug development, personalize patient care, and improve medical outcomes.
Scientific Publications
Perfect prosthetic heart valve: generative design with machine learning, modeling, and optimization
Excess mortality in Ukraine during the course of COVID-19 pandemic in 2020–2021
Use of semi-synthetic data for catheter segmentation improvement
A multi-reference poly-conformational method for in silico design, optimization, and repositioning of pharmaceutical compounds illustrated for selected SARS-CoV-2 ligands
Novel Efficient Multistage Lead Optimization Pipeline Experimentally Validated for DYRK1B Selective Inhibitors
AnFiSA: an Open-Source Computational Platform for the Analysis of Sequencing Data for Rare Genetic Disease
PyVaporation: A Python Package for Studying and Modelling Pervaporation Processes
Automatic Scoring of COVID-19 Severity in X-ray Imaging Based on a Novel Deep Learning Workflow
Indirect supervision applied to COVID-19 and pneumonia classification
Analysis of 329,942 SARS-CoV-2 Records Retrieved from GISAID Database
Quantori is excited to share research findings that are available on Cold Spring Harbor Laboratory's bioRxiv preprint server for biology "Analysis of 329,942 SARS-CoV-2 records retrieved from GISAID database"