The hype of ‘Digitalization’ in the pharma industry, virtually as a panacea, is palpable all around. It gives many a feel, directly or indirectly, that this one-time, resource-intensive, disruptive transformation would reap a rich harvest for a long time. In some way, good or bad, the sense of urgency underlying the hype, could possibly be akin to Y2K, that one witnessed before the turn of the new millennium.
Notwithstanding the current ballyhoo, the process of digitization in several Indian pharma companies began since quite some time and is now gathering wind in its wings. Several studies vindicating this point, were reported by the Indian media, as well. One such report of October 31, 2016 highlighted – even around 2013, a number of Indian drug players commenced adopting digitization. They mostly began with the use of modern technology for scientific detailing to doctors, often using algorithms for better insights into issues, like patient compliance. A similar trend was seen also in China, the report added.
Be that as it may, this article will explore whether or not ‘Digitalization’ is a panacea for all pharma business hurdles. Or, it is the backbone to build and maintain a patient-centric organization, with need-based subsequent giant technological leaps, for game changing sustainable outcomes. For better clarity of all, I shall dwell on this concept with AI as the next disruptive step, as it would play an increasingly critical role to be in sync with the customers of the fast-growing digital world.
Digitization is the bedrock to move forward with newer technologies:
That digitization is the backbone of AI adoption was brought out in the May 2019 paper by McKinsey Global Institute - titled, ‘Twenty-five years of digitization: Ten insights into how to play it right.’ It articulated, leveraging, and transitioning from, digital to new frontier technologies is an imperative, as several new frontier technologies are opening up, such as AI. It also spotlighted that early digitization is the foundation of AI deployment.
Elaborating the point further, the article wrote: ‘70 percent of companies that generate 50 percent of their sales through digitization are already investing in one AI domain. The evidence suggests that incumbents that have adopted AI early and are savvy about deploying these technologies have experienced strong profit growth. In effect AI is a new, higher- performance type of digital technology that may boost the ability of firms to accelerate their digital performance.’
No doubt, several hundred AI use cases would provide evidence of widespread benefits to operations and profitability for AI adoption. However, from the drug industry perspective, the possible dilemmas that will be important to understand, what factors are prompting faster adoption of AI in pharma. Besides, how to make out – what type of use of AI is likely to be most effective for an organization.
Regardless of the dilemma, the AI buzz is gaining momentum:
The fervor around AI is now peaking up, more than ever before. Regardless of the general dilemma – ‘what type of use of AI is likely to be most effective for an organization.,’ several companies are working on AI application in various areas. In sales and marketing domain, these include, improving customer interactions, maximizing product launches, understanding patient insights. This was also corroborated in an article, published by ZS on July 24, 2019.
Why is the AI buzz increasing in pharma?
The above paper identifies 3 broad elements for rapid increase of AI buzz in the pharma industry, which I am paraphrasing as follows:
- Data requirement for any meaningful business decision-making process has exploded, facilitated by increasing use of internet- based digital platforms.
- With the increasing digitization of virtually anything in everyday life, paper-based processes are fast disappearing.
- Realization of game changing impact of new AI algorithms with high degree of precision, on business.
As AI-based interventions are making a radical impact on everyday life, most pharma and biotech players are progressively getting convinced that it will eventually transform many critical areas of the business, despite a slow start.
AI can deliver much more than ever before, across pharma domains:
AI has a great potential to meet critical requirements of almost all domains of the drug industry. For example: AI may be used to help a medical representative get top insights for his particular day’s or a week’s or a month’s call with doctors by sifting through all his daily reports for that period. Some companies are already moving into this direction. For example, Novartis, reportedly, has equipped sales representatives ‘with an AI service that suggests doctors to visit and subjects to talk up during their meetings.’
Similar AI-based cognitive insights may be obtained from the patient-collected data in the apps or other digital tools. Deep understanding of the process of thinking of important doctors and patients, would facilitate developing customized content for engagement with them, and thereby help achieve well-defined goals with precision.
There are instances of significant success with the use of AI in R&D, clinical trials, many areas of sales and marketing, including supply chains. Nevertheless, the general concern of sharing confidential patient information, often limits access to requisite data for use in AI solutions. Appropriate regulations are expected to address this apprehension, soon.
Big Pharma players are already in it:
The paper – ‘Artificial Intelligence in Life Sciences: The Formula for Pharma Success Across the Drug Lifecycle,’ published on December 05, 2018 by L.E.K Consulting, discussed this point in detail. It says, ‘each of the major pharma players is investing in the technology at some level.’
For example, pharma and biotech majors, such as Novartis, Roche, Pfizer, Merck, AstraZeneca, GlaxoSmithKline, Sanofi, AbbVie, Bristol-Myers Squibb and Johnson & Johnson, are either collaborating or acquired AI technologies to acquire a cutting-edge in business.
The paper also reiterates, developments in AI applications are occurring across the spectrum of pharma business, from target discovery to post-approval activities to automate processes, generate insights from large-scale data and support stakeholder engagement. Let me illustrate this point with an example below.
Example of use of AI for better patient compliance, improving sales and profit:
As highlighted in my article, published in this blog on May 20, 2019, effective use of AI for better patient compliance, can help improve concerned company’s both top and bottom lines. I mentioned there: ‘According to November 16, 2016 report, published by Capgemini and HealthPrize Technologies, globally, annual pharmaceutical revenue losses had increased from USD 564 billion in 2012 to USD 637 billion due to non-adherence to medications for chronic conditions. This works out to 59 percent of the USD 1.1 trillion in total global pharmaceutical revenue in 2015.’
Several reports vindicate that drug companies are making phenomenal progress in this area. Let me cite an example of achieving huge success to improve treatment adherence of patients during clinical trials. The September 26, 2016 Press Release of AiCure, an AI company that visually confirms medication ingestion on smartphones, announced that use of AiCure AI platform demonstrated 90 percent medication adherence in patients with schizophrenia, participating in Phase 2 of the AbbVie study.
Opportunity to make more effective drugs faster and at reduced cost:
Besides, drug discovery, clinical trials, patient monitoring, compliance monitoring – AI applications have been developed for marketing optimization, as well. As AI technology spreads its wings with a snowballing effect, taking a quantum leap in organizational effectiveness, productivity and outcomes will be a reality for many. Moreover, AI now offers a never before opportunity of making novel, more effective and safer drugs, faster and at much reduced cost.
Thus, I reckon, AI-based technology would be a basic requirement of the drug industry for effective operation with desirable business outcomes, in less than a decade. Its slow start as compared to many other industries, notwithstanding. Further, the pharma industry’s endeavor for a swift digital transformation – the backbone of AI adoption, as captured in recent surveys, also vindicates this belief. Other business realities are also generating a strong tailwind for this process.
Pharma’s swift digital transformation to create a solid base for AI:
The ‘White Paper’, titled ‘Use of Artificial Intelligence and Advanced Analytics in pharmaceuticals’ by FICCI captured this scenario quite well. It pointed out, two seismic shifts in the pharma business, namely, – reducing prices and demonstrating greater value from their therapies, along with a swing from treatment to prevention, diagnostics and cure – are prompting the industry for a holistic transformation of business.
Which is why, pharma players are exhibiting greater intent for ‘Digitalization’ of business, paving the way for quick adoption of different modern technologies, such as AI and advanced analytics. This fundamental shift will not only improve efficiencies and reduce costs, but also significantly help adapting to more patient centric business models. Yet, post digital transformation the key question that still remains to be addressed – how does an organization identify and focus on the right areas or ‘good problems’ for AI intervention, fetching game changing outcomes, on an ongoing basis.
Conclusion:
There could be many approaches to address this situation. However, according to ZS, building the capability and the muscle first for AI, and then looking for the problems, may not be a great idea. This could make a company, even post ‘Digitalization’, flounder with the right applications of AI technology. Thus, while venturing into AI intervention for watershed outcomes, the top priority of an organization will be to resolve this dilemma for precise identification of the right problems.
These areas may even include crucial bottlenecks in the business process, AI interventions for which, would lead to not just incremental benefits, but cutting-edge value creation, for a giant leap in an all-round performance. The name of the game is to start selectively with the right problems, evaluate the upshots of AI use, before scaling up and adding new areas. Ongoing value creation of such nature can’t be achieved just by one-time digital transformation, sans imbibing other disruptive technologies, proactively.
This, in my view, has to happen and is practically unavoidable, primarily driven by two key factors, as below:
The first one was the focal point of the ‘2018 Digital Savvy HCP Survey Report of Indegene.’ It found, the highest jump of digital adoption by healthcare practitioners (HCPs) was seen in 2018, compared to its similar surveys done from 2015 to 2017, signaling physicians’ fast-growing digital preference, as we move on.
The second one comes from an important ‘consumer behavioral perspective.’ and is specially in India. According to a report by the Internet and Mobile Association of India (IAMAI) – with 451 million monthly active internet users at the end of financial year 2019, India is now second only to China in terms of internet users. More, importantly, the digital savvy customers are also using other disruptive technologies, mostly smartphone based.
Thus, disruptive digital transformation in pharma domains, including sales and marketing, is a necessary basic step. It will help companies being all-time ready to imbibe other leading-edge technologies, such as AI, for giant leaps to higher growth trajectories.
By: Tapan J. Ray
Disclaimer: The views/opinions expressed in this article are entirely my own, written in my individual and personal capacity. I do not represent any other person or organization for this opinion.
