How Artificial Intelligence Is Helping The Pharmaceutical Industries?

The current drug discovery process needs to shift dramatically in order to meet the needs of both the society and patients in the 21st Century. Artificial Intelligence and machine learning, in particular, present the pharmaceutical industry with a real opportunity to do R&D differently, so that it can operate more efficiently and substantially improve success at the early stages of drug development. There needs to be a fundamental shift in drug discovery and Artificial Intelligence holds the key to bringing the pharmaceutical industry into the 21st Century.

Long Term Benefits

The long term benefits of this will mean that the vast resources and money used to develop drugs in the current process will be deployed more effectively to give not only a better return on the investment but also a substantial increase in the delivery of new medicines for serious diseases.

Pharmaceutical companies have vast amounts of compounds that could be the perfect solution to combat specific diseases, but they have no way to identify them as such. The development and production of drugs can cost pharmaceutical companies up to $2.6 billion (£1.8 billion) and take 12 to 14 years to complete.

Reduced Time and Cost

Thus, the main short/medium-term implication AI has for the pharmaceutical industry is the reduced time it takes to develop drugs and thus the associated costs, enhancing return on investment and could even mean a reduction in cost for end users. It can take up to 15 years to translate a drug discovery idea from initial inception to a market ready product. This contrasts with the rapidity of innovation in other industry sectors. Identifying the right protein to manipulate in a disease, proving the concept, optimizing the molecule for delivery to the patient, carrying out preclinical and clinical safety and efficacy testing are all essential, but ultimately the process takes far too long.

Technology

Technology will drive the Pharmaceutical Industry Forward One highly advanced tool that leaps to the forefront of this discussion and illuminates the possibility of what technology holds for our industry can be stated as a clinical report writing tool based on artificial intelligence.

In less than an hour, this tool can generate a first draft, company and regulatory-compliant Clinical Study Report (CSR) that is 80% to 90% complete. Let that sink in for a moment. In less time than most people take a lunch break, there is a tool that successfully drafts a fully compliant, 80% to 90% completed CSR.

This tool can reduce the time for completing each CSR by four to six weeks, and can reduce the internal resource utilization per the study by about 250 hours and about $25,000. Researchers at Houston Methodist Research Institute have developed an AI model that can predict breast cancer risk, allowing doctors to closely monitor those at future risk Processing large clinical and medical data isn’t the only place where AI could affect the pharmaceutical industry.

Methodology

Even business and marketing based decisions could be helped by computing ‘brains’, for example by analyzing and assisting with mergers and acquisitions and providing guidance on the most efficient and effective way to market new products. The technology will also help in terms of the industry’s selection of patients for clinical trials and enable companies to identify any issues with compounds much earlier when it comes to efficacy and safety.  The AI and machine learning methodologies could contribute a lot to the development of the industry. It can be used to good effect to build a strong, sustainable pipeline of new medicines. A group of researchers who are experts in hypotheses arrives at a prioritized list of hypotheses which are considered to be worth exploring.