BenevolentAI: From Machine Learning Startup towards New Drug Producer
BenevolentAI is using machine learning to gather insights from the body of pharmaceutical literature in order to produce new potential drugs, but can it keep top talent?
drug development process
Navigating Drug Discovery using AI
After the boom of Blockbuster(drugs with revenues exceeding $1B/yr) approvals in the 90’s, there has been a slowdown in the development of new drug entities (NDE). With drugs already in the market for easy to identify targets, research in academia […]
Roche: Improving Drug Discovery and Development with Machine Learning
Machine learning has been touted as a potential cure-all for high drug prices. A number of leading biopharmaceutical companies like Roche have made some large bets in using artificial intelligence tools to improve drug development, but it remains to be seen if machine learning is living up to its hype.
Beyond the Pill: Teva’s Use of Digitization to Add Value Back into Generic Drugs
Connected drug delivery devices are among the many digital supply chain innovations Teva has acquired to drive sales and control operational costs
Clinical Trial Recruitment at Acurian in a Digital Age: Lives and Millions of Dollars are at Stake
Clinical trial delays can result in lost revenue to drug firms of $600k – $8 million per day, not to mention additional lost lives as life-saving treatments wait in the wings . Patient recruitment is the number one cause of clinical trial delays and cost overruns, and Acurian has led the digital transformation of the recruitment process. The Company better identifies and targets appropriate populations through its 17 million patient database and population mapping algorithms [8].
Evaluating New Drugs with Wearable Technology
Can wearables and electronic data capture (EDC) technologies improve clinical trials and accelerate new drug approval?