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Human "Intelligence" in the form of qualified human resources has been the key component in driving the growth of the pharma industry domains. The industry has been a "blessed" industry with a vast talent pool in the current Century. This is on account of reputed institutions offering a range of pharmacy courses at graduate & postgraduate levels.
The industry growth however has been fluctuating in the last 10-12 years on account of various factors like rising disease (known & unknown) prevalence. rising competition, raw materials prices (bulk & API), changing regulatory environment and to some "shortage" of labour in the manufacturing domain & the impact of pandemic (Covid-19) to name a few.
To cope up with the increasing challenges and to ensure sustainable profit margins, pharmaceutical industry has been exploring Artificial Intelligence as an alternative to "human intelligence" in some of its selected business processes like drug discovery and manufacturing.
Artificial intelligence (AI) adoption by the pharmaceutical industry has led to increase in efficiency & lowering of costs thereby having a direct impact on human intelligence.
Overview and trends in uses of AI
The pharmaceutical Industry has very complex value chain and has been facing many challenges in the last decade on account of both known and unknown unpredictable factors.
However, there are three segments of the pharmaceutical industry where artificial intelligence has an extensive usage and application:
1. Drug discovery, clinical trials & diagnostics
2. Manufacturing
3. Drug Distribution
A detailed outlook in the application of artificial intelligence in each of the above three segment at the micro level is as follows:
Drug discovery, clinical trials & diagnostics
a) AI helps in “easy identification of the drug target for a particular disease therapy. AI can analyse large data sets and molecular patterns to discover new molecules and compounds and simplifies the process of synthesizing these compounds.
b) AI applications in diagnostics helps in screening existing patient data quickly and helps identify an accurate diagnosis; development of personalized treatments with predictive computer models.
c) Optimization of clinical trials by identifying major challenges in patient recruitment right from the patient identification to the patient enrolment thereby enhancing the speed of the drug development process.
d) Patient adherence and to treatment and reduction dropout rates of prescribed medications.
e) Drug repositioning/Drug re-purposing: Pharmaceutical Industry is utilizing AI to explore various pathologies/disease areas where the existing drugs/medications can be used. With the systematic reuse of these drugs, risks can be reduced and the development process can be speeded up.
Pharmaceutical manufacturing
a) In pharmaceutical manufacturing, AI helps in Improving drug quality during manufacturing and compliance with standards (elimination of defects in real time).
b) AI helps proactive detection of safety risks either to people or to the business in the Pharma manufacturing plants. AI can monitor access of people and vehicles to restricted areas or areas with a high risk of contamination. AI systems can stop equipment and machines automatically to ensure safety.
c) Enhancement of production visibility by identifying bottlenecks, which impacts productivity and quality, estimate inventories, verify product packaging, and prevent or anticipate machine failures. AI help in providing a continuous flow of information which improves process visibility for making real-time decisions.
Distribution, commercialization & marketing
a) AI can successfully predict the demand of medicines/drugs, help in optimizing logistics and inventory.
b) AI can detect and predict trends of new products, which makes it possible to cross-reference drug sales variables with user preferences.
c) AI systems can analyse drug purchasing and supply patterns to detect fraud and abuse in the pharmaceutical market.
d) AI helps in managing communication with virtual assistant support and through new channels
Six out of the 12 collaborative explorations of the pharmaceutical industry in AI are in drug discovery citing the needs of newer drugs for the emerging newer diseases and for the existing & rising diseases of the global population.
India pharma industry and AI adoption
AI has been present for quite some time in India. However Indian pharmaceutical companies are still exploring & evaluating its capabilities and how it can aid in uncovering new insights and enhancing the effectiveness of product sales. The integration of AI into the pharmaceutical sector holds tremendous promise for shaping a brighter future in healthcare and beyond. Integration of AI into the Indian pharmaceutical sector holds tremendous potential for shaping a brighter future in healthcare and beyond.
According to a recent survey conducted by E&Y, a major portion of Indian companies (53 per cent) are in the "beginners" stage of AI implementation, while 40 per cent are categorized as "conservatives," and only a very small fraction (7 per cent) has moved to the "explorers" stage. In the Indian pharmaceutical there has been a shift from manual to digital processes in the last few years but there is a perceived lack of added value, according to a few industry experts.
Innovative start-ups lead the way
Many emerging start-ups have gauged the opportunity in the Indian pharma sector and have developed novel inventions to help the industry cash in on the opportunity provided by AI. The Covid-19 pandemic has enhanced an active adoption of e-pharma services as people turned to online platforms for their healthcare needs.
In the last few years, the e-pharma space in India has seen significant competition among various platforms, with several notable startups placing their presence in this segment. Key players are PharmEasy, Medlife, Netmeds, 1mg, etc. to name a few. Further, the share of sales for OTC companies from e-commerce platforms has also increased.
McKinsey Global Institute in an article titled “Generative AI in the pharmaceutical industry: Moving from hype to reality” published January 2024- has estimated that Artificial Intelligence could generate $60 billion to $110 billion a year in economic value for the pharma and medical-product industries , mainly because it can boost productivity by accelerating the process of identifying compounds for possible new drugs, speeding their development and approval, and improving the way they are marketed.
According to a PWC report titled “Re-inventing Pharma with artificial intelligence, pharmaceutical companies are in the race to seize the $250 billion AI opportunity by 2030. The three major areas where AI would make a major impact are:
1. Operations which would account for 39 per cent of the impact by boosting efficiency on the production, material, and supply chain costs
2. This is followed by R&D which would account for 26 per cent of the impact, followed by commercial at 24 per cent, with AI increasing efficiencies in developing new medicines and opening new ways of interaction
3. Pharma’s support functions would contribute 11 per cent, with AI increasing the speed and efficiency of supporting processes such as IT, finance, HR, and legal and compliance.
Availability of dedicated courses on AI
Artificial intelligence (AI) is enhancing the convergence of pharma, broader healthcare, technology, and consumer products and generates great benefits for each sector. To leverage the benefits, there is a dire need for pharmaceutical companies to take steps to enhance “people “skills and alternatively hire individuals with relevant domain skills in artificial intelligence. However, in the current scenario, the availability of human resource with domain expertise to tackle challenges with AI in pharmaceutical industry is very much in the nascent stages in India. The reason for the same can be attribute to the following:
Availability of only short term and basic courses (mostly online) from both certified and non-certified institutions. Many startup education focussed companies like https://www.udemy.com/, https://www.upgrad.com/ & https://www.careers360.com/ to name a few are offering courses with video tutorials to online training up to six months. Many institutions have been claiming affiliations with global tech companies in their offerings. Tracking the “Validation” on the methodology of the AI course delivery and its utilization in the pharmaceutical industry is currently robust. Only online reviews and ratings based on user experience are available which are generally used by the companies offering the courses for their marketing promotion activities.
(Author is Market Research Consultant)
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