The growing demand for ML/AI technologies, as well as for ML/AI talent, in the pharmaceutical industry is driving the formation of a new interdisciplinary field: data-driven drug discovery/healthcare. Consequently, there is a growing number of AI driven startups offering technology solutions for drug discovery/development. In drug development, preclinical phase (in vitro and in vivo), also named preclinical studies and nonclinical studies, is a stage of research that begins before clinical trials, and during which important feasibility, iterative testing and drug safety data are collected. According to a detailed mind-map prepared by Pharma Division of Deep Knowledge Analytics (updated Q1 2019): the AI for Drug Discovery, Biomarker Development and Advanced R&D Industry Landscape counts so far 400 investors, 170 companies and 50 corporations. This article focuses only on the AI startups and the AI investors trying to overcome the above 4 challenges during design and execution of the preclinical phase.

We are a team of scientists, engineers, designers, and developers with offices in London and Boston and together we've developed the DESKGEN platform for CRISPR genome editing. Founded in 2012, Desktop Genetics is venture backed by some of the UK's leading life science thought leaders and supports customers in the UK, USA, Japan, and beyond. As a Machine Learning (AI) Scientist, you'll work to translate the latest CRISPR research into software that powers the experiments of thousands of labs. The application of artificial intelligence to genomics is a rapidly evolving field currently at the forefront of research. The work is highly interdisciplinary and successful candidates will have experience or advanced training in aspects of computer science, data science, engineering, biology, statistics, mathematics, or machine learning.