Bringing drugs to markets faster using AI: Interview with Manish Gupta, CEO, Indegene
27 APR, 2020
Manish Gupta, CEO of Indegene, talks on how Artificial Intelligence (AI) could play pivotal role in hastening conventionally slower processes, such as clinical trials and regulatory submissions, to deliver drugs faster to patients, while bringing down the costs of sales & marketing for lifesciences and pharma.
The world is continuing to battle one of the biggest humanitarian crises known to mankind, with norms like social distancing and wearing masks having disquietingly become a part of life, at least for the foreseeable future. Even as we practice these social measures to ensure safety from COVID–19, the clock is ticking on a vaccine. At a time like this, could AI play pivotal role in hastening conventionally unhurried processes such as clinical trials and regulatory submissions and delivering drugs faster to the patients?
Indiaai’s Sindhuja Balaji talks to Manish Gupta, CEO of Indegene, a global health tech company focused on lifesciences that leverages AI technologies to enable speedier drug discovery, product commercialisation, acceleration of regulatory processes, safety tracking and reporting, real world data gathering from digital devices and EHRs, speedier product/drug launch in markets, and superior customer experience.
Tell us about the role of AI in pharma today and its possible impact on the sector?
AI in Healthcare and Pharma has tremendous applicability. It will alter existing processes, transform how goals are achieved, probably make some of the established processes redundant. We see the Pharma industry using AI in every area critical to its existence such as drug discovery, clinical trials, supply chain and delivery, regulatory submissions, etc. One of the key areas where Indegene uses AI is sales and marketing. Pharma companies spend about 25% of their revenue on sales and marketing activities, this is where we believe AI can make a significant impact.
How is Indegene leading the efforts of introducing AI in different areas for pharma?
In India, we benefited from lifescience companies outsourcing pharmacovigilance or drug safety processes, which was fairly standardized with IT companies. We have a significant solution to automate pharmacovigilance processes. These include voice recognition from customer calls, automated voice–text conversion, processing of crucial data from emails and faxes using NLP, and the like.
We are even more excited about using AI in the drug regulatory process with significantly higher impact. It is especially helpful for drugs that need to be expedited—for instance, the COVID–19 situation. The use of AI in crucial processes of drug regulation could include increasing probability of first–time success upon submission of documents and consequently shortening the cycle time to getting regulatory approvals. Some of our AI-based solutions currently deployed in pharma companies as pilots are showing extremely promising results.
The other big area we are partnering with the industry is medical content. While the industry is organized into clinical, regulatory, safety, medical affairs and commercial silos, the reality is that drug and disease content are fundamentally the same. This content is assembled and presented in different ways to achieve different objectives–for example, seeking regulatory approvals from FDA, getting a drug listed on a formulary, or convincing a physician of the therapeutic use and superiority of a drug etc. The lifesciences industry sells content, not the drug itself. The solution we are developing leverages AI to ultimately accelerate time to agency and market, increase velocity and drive personalization of communication to various stakeholders.
One of the other areas we use advanced technology is in managing drug labels in global markets. We use a combination of AI, NLP and Computer Vision in these areas for ensuring regulatory compliance. We also use AI to enable faster responses to physician queries for overall improved patient care.
We have highly experienced in–house technology and medical teams and we also partner with tech majors like Microsoft, Google and Amazon for synergies.
How do you arrive at optimum drug commercialisation through technology? How do the two areas converge?
Just over a decade ago, we identified sales and marketing in lifesciences as one of the big areas that could be impacted by technology. Sales and marketing cost was 25% of revenues and primarily consisted of medical reps interacting with physicians. Given the proliferation of channels, ease of access to content, and also regulatory pressures on physicians and lifesciences for fair marketing practices, we believed technology would play a significant role in the new–age drug sales and marketing. Since then, we have made significant investments in tools, capabilities and partnerships to build a compelling offering. We approach co–commercialisation using digital means with the aim to accelerate product adoption by bringing analytics, content, channels capabilities together. We currently handle a portfolio of products in the US that are aggregated at a billion dollars, and driven by technology–guided sales and marketing programs. We work with a range of small, mid-size and large pharmas as well as biotech companies. We also work on a range of pharma–related products that are in different stages of lifecycle.
What would you say are your company’s best practices/key strategic approaches to stay ahead when it comes to adoption of digital practices?
We are not a horizontal company. We don’t think on the lines of “what can we do with AI?” We have always thought from an industry pain–point perspective and then worked backwards to build soutions and products to solve those pain–points. A decade ago, when digital and AI were not the buzzwords as they are today, we built solutions to use digital as the central piece for driving up sales and developing the market. AI came along and augmented our efforts in this endeavour. What I believe has helped us is our ability to work backwards from a customer standpoint and then augmenting technology or domain capabilities, where needed. We also have been open to partnerships with technology companies. The synergy is two-way—companies that build horizontal tech need partners that are domain–rich, possess sector expertise, and understand how technology can supplement their core offerings. It is crucial to think about this when you design an organisation and how you would like to stay differentiated.
How do you think data analytics will positively impact the overall lifesciences industry?
We have helped lifesciences companies tailor processes with the help of strategic marketing, forecasting and market intelligence, and various other processes. Despite these offerings, we believe standalone analytics cannot deliver full impact due to lack of ownership of the full process. We thought it would be better to drive impact by introducing analytics-driven models as part of our overall offerings to drive outcomes.
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