AI Articles and Analysis about Drug discovery

In the fields of medicine, biotechnology and pharmacology, drug discovery is the process by which new candidate medications are discovered.

V.1 – How AI Drives Drug Development Workflows and Value Chains Across Life Sciences Enterprises-1x-min

How AI Drives Drug Development Workflows and Value Chains Across Life Sciences Enterprises – with Leaders from Benevolent and Takeda

This article/interview analysis is sponsored by BenevolentAI and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Driving Drug Discovery Efficiencies in Life Sciences with AI-1-min

Driving Drug Discovery Efficiencies in Life Sciences with AI – with Anne Phelan of BenevolentAI

According to research from the American Society for Biochemistry and Molecular Biology, nine out of 10 drugs fail to make it to market in the clinical trials process. Researchers in the cited studies found that 40-50% of these failures are due to a lack of clinical efficacy, meaning that the drug is not able to produce its intended effect in people, and 30% were due to unmanageable toxicity or side effects.

Overcoming Cultural and Technological Hurdles for AI Integration in Life Sciences-1-min

Overcoming Cultural and Technological Hurdles for AI Integration in Life Sciences – with Daniel Ferrante of Deloitte

Far beyond surface-level 'chatbot' software, and other customer-facing support systems, the same generative AI (GenAI) capabilities having direct impacts across language workflows in front-office tasks in financial and legal services is also having a direct impact on how research teams in the life sciences space are targeting solutions for rare diseases and novel treatments. 

Header graphics – Sanofi-1-min

Artificial Intelligence at Sanofi

Sanofi is a global healthcare and pharmaceutical company. Founded in 1973, it aims to unlock and maximize the potential of critical medicines, vaccines, and self-care solutions for individuals. It accomplishes this across four global business units: Specialty Care, Vaccines, General Medicines, and Consumer Healthcare. 

AI Opportunities for
Life Sciences R&D-1

AI Opportunities for Life Sciences R&D – with Andrew Bolt of Deloitte

This interview analysis is sponsored by Deloitte and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

final-updated-Approaching Life Sciences and Retail Challenges from a Data Perspective – with Alberto Rizolli of V7

Approaching Life Sciences and Retail Challenges from a Data Perspective – with Alberto Rizzoli of V7

Problems in different industries can look quite similar when looked at from the perspective of data. Though diverse business problems originate from distinct domains and needs, they often share a common thread and solution. 

AI at Takeda@1x-min

Artificial Intelligence at Takeda Pharmaceuticals

Takeda Pharmaceuticals is a 240-year-old, leading biopharmaceutical company headquartered in Tokyo, Japan, with a global hub in Cambridge, Massachusetts. The company has a global presence, operating in more than 80 countries across North America, Europe and Asia.

Future of Drug Targeting – Lilly @2x-1-min

The Future of Drug Targeting and Clinical Development with Generative AI Tools – with Ramesh Durvasula of Eli Lilly

Lily is a pharmaceutical giant with a legacy dating back to its founding in 1876 by Colonel Eli Lilly. The company engages more than 9600 employees in research and development, with clinical research conducted in more than 55 countries. As of 2022, the company clocked a revenue of $28,541.4 million and made a net income of $6,244.8 million. 

Drug discovery

In the fields of medicine, biotechnology and pharmacology, drug discovery is the process by which new candidate medications are discovered.