Reimagining commercialisation with AI
Indegene hoping to address them?
One big goal for us has been to modernise the pharma sales and marketing model and allow companies to commercialise their products in a much more efficient and effective way.
Pharma has traditionally been very focused on using a rep-led model, typically building channels and slowly moving into digital data. But based on the pressures we've seen from a pricing point of view, from consumerism and the way consumers are reacting, we think that pharma will have to reinvent itself.
In big pharma, the cost of sales today is extremely high. It's between 28% and 30% in a traditional rep-based model. It's very difficult for a large pharma company to reach out to 100,000 doctors or more using this model. It's unsustainable.
Meanwhile, there are also many new biotech companies who do not know how to commercialise products very effectively. We think it's a good time to help them leapfrog the traditional method to a new-generation model.
We have built an AI-led platform, using an omnichannel ecosystem, that can help pharma to commercialise more effectively, using advanced analytics for customer segmentation, targeting and then building sequencing and predictive analytics to drive certain cohorts for prescription. It's a digitally led platform rather than a rep-led platform.
Do you feel like smaller and newer pharma companies are more open to this kind of change than big pharma companies?
Definitely, yes. We are finding most of our traction in new generation biotechs, digital therapeutics, or value-added generics companies.
They are much more open because they typically do not have a large supply of cash for launches. They want to create more value for their investors because they're heavily funded by private equity. They are looking for a much better way of stretching their dollars.
The other sweet spot here is young pharma companies that are going to hit peak sales of around 100 to 400 million. If that's the range, below half a billion, this is a fantastic model compared to a rep model, because in a traditional rep model it's very difficult to break even or make money if you put 300, 400, 500 reps on the ground.
That said, with some of the new leadership coming in, big pharma is also becoming more open to experimenting with this. They are running pilots with us in mature brands. Four to five years after launch, when you're moving towards a much larger upselling audience, you can go to another 100,000 doctors with the drug, but it's harder to use the rep model to cover those 100,000 physicians.
How does the AI aspect of the platform function?
The platform consists of two parts. One is targeting of doctors, which we have built based on segmentation. Targeting the right customer with the right channel and the right technology is where AI can really shine.
The platform creates HCP cohorts based on channel, frequency, day, date, content, connection. Based on that, it comes up with a predictive algorithm of what will drive a customer journey.
Customer journeys are typically not linear and sequential in the pharma world. The art of selling is all about delivering sequential, linear journeys. What we have shifted to is the science of selling. In the science of selling, the machine predicts what the doctor's next few touch points are going to be and tells you what the content should be and how it should be delivered.
The second part is how you measure and optimise using AI. How do you use these analytics to actually see whether this is working? If those haven't worked, then what's the next possible journey you should take? The platform can give these recommendations.
How would you like to see the technology develop? More generally speaking, where do you see the future of the company going in the next few years?
By building intelligent customer engagement, which includes patients and doctors, we can move towards precision marketing. We're now looking at how patient engagement and patient adherence can be fully selected, so that we can close the loop with patients. We could also use data like electronic medical records to find the right people for the right treatment, to make sure the right treatment is administered in the doctor's room.
With things like gene therapy and precision medicine there's going to be a completely new generation of discovery methodologies coming in over the next five to seven years. The way that drugs are discovered, distributed and commercialised will be very, very different. Meanwhile, there is increased pressure on pricing from governments around the world, which will have an effect on profit margins. The biggest cost for them today is sales and marketing.
Pharma will need to completely reinvent itself. Indegene wants to be able to shape the future for pharma – that's our goal and that's the place where we are continuously investing to make sure the industry is able to build new models.
About the interviewee
Gaurav Kapoor is executive vice president – business development & strategic client partner at Indegene. He has more than a decade of experience in the pharma industry in various positions, including product management, international marketing, marketing management, and general management. Prior to Indegene, Gaurav was managing the cardiovascular product portfolio at Torrent Pharmaceuticals
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