“Innoplexus is not just a business but a mission to create an impact”

Dr Gunjan Bharadwaj,
Founder and Chairman,
Innoplexus focuses on product development for Big Data Analytics. The company helps in the future of how data is curated, analyzed and consumed by disrupting prevailing processes through cutting edge technology, innovation and a superlative ability to understand business challenges. Dr Gunjan Bharadwaj, Founder and Chairman, Innoplexus shares his Views on Data Analytics scenario in India and Globally and How Data analytics is enhancing accuracy and cost cutting in Pharma and Lifescience sector, in an email interaction with Mahesh Kallayil.

Could you please tell us about Innoplexus'offering to Pharmaceutical industry?
Innoplexus is on a mission to fundamentally transform the way data and analytics is produced and consumed in the Pharmaceutical Industry. With growing volumes, veracity and velocity of data; the future cannot be hundreds of analysts curating data manually and selling it at a significant premium to Pharmaceutical companies and Healthcare players. Smaller and medium sized players do not even have the resources to get such services. Imagine the inefficiencies when one cannot look at the competitive landscape in an environment where change is accelerated. Innoplexus with its Data as a Service platform iPlexusTM is providing real time decision support not only to Big Pharmas but also Research Institutes, Treatment centres, Investors and a number of small biotech. This platform crawls and analyses hundreds of terabytes of data from the external environment in real time for decision support. Similarly, in Analytics as a Service offerings; even for use cases where decision support follows a repetitive schema, traditional offerings are all about positioning analysts. This is not scalable given that enterprise data is exploding at a tremendous pace. Our Continuous Analytics as a Service applications triangulate enterprise data with external data in real time providing decision support for various use cases. Be it repurposing your drug candidates, discovering Key Opinion Leaders, identifying biomarkers or any other use case - why should Pharmas be satisfied with one off projects and decision support through static presentation slides?
How does Innoplexus differentiate themselves from their competitors?
Innoplexus differentiates itself on three counts. First we believe in full automation, second is the breadth as well as depth of the data we cover that continues to increase each day and thirdly our emphasis on continuous decision support. Decision makers ought to get decision support where and when they need it.
Please share your views on Data Analytics scenario in India and Globally
Data Analytics is going to grow at a tremendous pace in India as well as globally. However, the focus going forward is clearly going to be automation. DaaS and CAaS applications would eventually also empower startups in the healthcare space to create real innovations. Healthcare is one area that requires novel solutions for India. Copying and pasting models from abroad won't always work for Indian scale and reality. Innovation in India has to happen in Healthcare! We need to empower physicians working tirelessly in rural and semi-urban settings as well as Researchers to research as well as start enterprises in India rather than going abroad. Government is playing a tremendous role in facilitating the same but the onus is on entrepreneurs like us!
Do you think life science industry is still dubitative about how to use and make the most of the new IT scenario? Why is that?
Life Sciences Industry has the same inertia as others. I would look at this inertia with respect to two aspects : (1) Traditional paradigm of decision support (2) Traditional Organisational Design of IT organisations. (1) Traditional paradigm for decision support: The order of complexity in the pharmaceutical market has increased substantially. Regulations are tightening in various key markets capping the pricing power of pharmas. This also limits the returns to innovate - given the limited period of market exclusivity that is followed by Gx competition. Relatively smaller patient populations is a challenge for clinical development as centres remain dry of patients but regulatory agencies remain clawed to traditional ways. Real World Evidence remains a distant dream. A lot of investment gravitates in Oncology and Neurology, drying up Research & Development in other therapeutic areas where with sheer number of patients, its possibly needed more. Mortality rates related to diseases in other therapeutic areas, if treated and managed well, have come down drastically. New drugs in these areas cannot promise substantial value over existing treatments, hence the returns for Pharma companies in these therapeutic areas are also limited. On the other hand, more investments would not mean higher success rates in Oncology and Neurology. There will be a limited number of R&D assets and capabilities including people in these TAs that these investments will chase. In addition, statistically there is a limit to innovation throughput. This means by increasing the number of drug candidates in the beginning of the innovation funnel, one cannot get a higher number of successful drugs out in the end. In emerging markets, market access remains a big challenge as well. Pharmaceutical companies are trying hard to address this increasingly complex market reality. However, the decision making remains a batch process. Decision support even for repetitive challenges is one off and requires manual effort, be it from internal teams or outside consultants. External environment is tracked using expensive manually curated data feeds and analytics for decision support is typically a dumb dashboard if not a slide deck affair. This takes time to change as executives still have old ways and time tested relationships with existing providers. (2) Organisational Design of IT Organisations : For new digital models one needs a skunkworks approach. Colleagues need to learn new technologies fast as older ones get obsolete. One needs rapid prototyping and close interaction as well as understanding of the businesses. This doesn't mean that the traditional IT is not useful anymore. However, it does mean either IT organisations need to embrace ambidexterity to balance the exploitative and exploratory nature of work or one needs to house the digital skunkworks outside the existing IT Organisations. It is also about the performance management frameworks and reward systems. Disruptive solutions need to be recognised and rewarded differently; only then can one have and retain the best in class talent in organisations.
How Data analytics is enhancing accuracy and cost cutting in Pharma and Lifescience sector?
Data analytics is driving value across the entire value chain from discovery to commercialisation. Industry is embracing automation in all aspects. This has Traditional business models of Data Services and Analytics as a Service have to reinvent themselves. With growing volumes, veracity and velocity of data; the future cannot be hundreds of analysts curating data manually and selling it at a significant premium to Pharmaceutical companies and Healthcare players. Smaller and medium sized players do not even have the resources to get such services. Imagine the inefficiencies when one cannot look at the competitive landscape in an environment where change is accelerated. Innoplexus with its Data as a Service platform iPlexusTM is providing real time decision support not only to Big Pharmas but also Research Institutes, Treatment centres, Investors and a number of small biotech. This platform crawls and analyses hundreds of terabytes of data from the external environment in real time for decision support. Similarly, in Analytics as a Service offerings; even for use cases where decision support follows a repetitive schema, traditional offerings are all about positioning analysts. This is also not scalable given that enterprise data is exploding at a tremendous pace. Our Continuous Analytics as a Service applications triangulate enterprise data with external data in real time providing decision support for various use cases.
Please elucidate us on the Importance of machine learning and artificial intelligence for Life Sciences sector?
AI has been misused by many enterprises to 'free ride' the wave. Many a times its used recklessly and interchangeably with Machine Learning. AI offers significant promise for the future. It is critical to DaaS and CAaS or any business model that envisions complete automation. We see driverless cars on freeways in California and AI based approaches predict treatment options. In India, we need innovation in automating diagnostics and treatment decision support for improving healthcare access. AI holds significant promise, but a lot needs to be done. We use both AI and ML in our Data as a Service Platform iPlexusTM and in many of our Continuous Analytics as a Service offerings, the real time analysis of data with high velocity and variability mandates AI for scale.
How Data Analytics has reached to next level and used widely with the help of Artificial intelligence?
Traditional approaches based on manual curation or stop gap arrangements using some tools using manual intervention cannot provide scale with increasing volume, velocity, variability and veracity of data. Decision makers need decision support at the time and platform of their choosing. It needs to be continuous and real time. AI holds promise for that new paradigm of decision making.
How Data analytics helping Pharma & Life Sciences companies to make wise decisions?
Data analytics provides companies in the Life Science Industry with decision support throughout the value chain from discovery till commercialisation. Be it discovering Key Opinion Leaders at a specific stage of the drug, understanding the competitive landscape, discovering new biomarkers or promising pathways, looking at possible drug repurposing options, right trial designs, regulatory strategies as well as field force sizing and channel mix during or post launch - data analytics is critical for all decisions.
Which are the prominent and focused sector for Innoplexus in India?
Innoplexus is not just a business but a mission to create an impact. We want to democratise data and analytics, improving its reach to various stakeholders in the industry no matter big or small. We have recently concluded an MoU with Regional Cancer Centre, Gwalior to provide physicians with real time intelligence on discovery as well as clinical development and to assist them with tapping the power of analytics.
How iPlexus and KPlexus are useful for the enterprises?
iPlexus provides real time decision support with respect to the competitive l andscape of a drug or a therapeutic area as well as a specific company, biomarker, protein, pathway or gene. It covers enormous breadth of data that continues to increase each day. Enterprises can know about any development in their area of interest in real time. kPlexus is world's first real time Key Opinion Leader discovery and management platform. An enterprise can discover KOLs, can view the updates on their work, manage interactions as well as identify emerging players for specific use cases in real time. Various enterprise data sources such as ISS/IST databases, CRM etc. can be integrated into the platform seamlessly.
Is DaaS (Data Analytics as a service) a workable model in India?
Given the cost of manually curated databases and consulting based decision support business models, DaaS is the only way going forward to provide intelligence to Indian enterprises and stakeholders.
Is Innoplexus in talks with any new company/government hospitals for providing services?
Our team is keen to partner with Government and Government institutions to leverage our platforms and technology to improve healthcare and healthcare outcomes for our citizens. Also, our strategy of building a Continuous Analytics ecosystem of applications on our iPlexusTM DaaS platform makes partnerships key to our growth. We want to collaborate with different companies to use our data and solve different problems to eventually improve health outcomes.
Innoplexus recently raised pre series A fund from HCS, what are the plans for next round of fund raising ( Timeline and tentative amount)?
We are speaking to a number of interested investors and partners to help us grow further in key markets and build our IP. We may close the next round this year.
What, in your opinion, are the challenges in regulation that need to be addressed?
We respect data privacy and protection rules as well as guidelines of all geographies our clients operate in. In India, specifically we need to work on unified patient registries to track healthcare outcomes. It remains a big challenge with data security and privacy related concerns - however its the need of the hour. We cannot sharpen policy tools, understand outcomes and assess performance of healthcare delivery centres until this is done. India has the potential to become the largest Real World Evidence data goldmine. We need to also invest in rule based diagnostics for better screening at the last mile of healthcare delivery. All these themes present significant regulatory challenges for enterprises with respect to data security and governance in general.
What are the hurdles before Innoplexus in its march towards its goal of helping organisations move to continuous decision making by generating insights from structured and unstructured private and public data?
We need to remain agile than the competition and continue to scale fast - a challenge that's faced by all enterprises of our size. As Andy Grove said, "Only the Paranoid survive".
What are the future plans of the company in India and globally?
We want to be the DaaS standard with iPlexusTM platform in Life Sciences Industry, being a partner of choice for all stakeholders. We want to build a comprehensive application ecosystem on top of this platform partnering with different players. Doing this, we believe it is very important to also provide data and analytics access also to small and medium sized players. In the next few months, we will also start scaling our first pilots in other industries, especially the Financial Services Industry.