Table 2 Expectations and strategies of using AI in pharma industry

Expectation 1

Development of new drugs and biomakers

 Novartis

In order to categorise digital images of cells treated with new chemicals and group the compounds with similar effects, Novartis is employing machine learning [27]

 Berg

In more than 1000 cancer and healthy cell samples, an AI model was created to reveal previously undetected cancer pathways [27]

 Wuxi NextCODE

Medicines that are developed and evaluated in clinical trials using powerful pattern recognition [27]

Expectations 2

Tackling of diseases which were difficult to treat earlier

 Mission therapeutics

AI-assisted drug development for Deubiquitinase (DUB) inhibitors to combat Alzheimer’s and Parkinson’s [27]

 Helax

Utilizes HealNet, an AI platform that helps scientists to identify more drugs for diseases while at the same time minimising pain, expense, and danger [27]

Expectations 3

Drug adherence among volunteers during clinical trials

 CURATE

By optimising treatment dosage at the level of specific pattern, an AI-based platform was developed to halt the progression of advanced cancer disease [27]

Expectations 4

Better analysis and utilization of clinical data

 BenevolentBio

Knowledge graphs are created using an AI platform that receives data from sources including academic papers, patents, clinical trials, and patient records [27]

Expectations 5

Finding the correct patients for clinical and reducing turnaround times

 Santen and twoXAR

A platform for the discovery, screening, and prioritisation of novel medication candidates for ocular disorders was developed using AI [27]