Question: You joined Excelra in 2014. Tell us a little about yourself, your background and how you became involved with Excelra?
Anandbir: I have been involved with Excelra right from its inception in 2014 as part of the team that identified the original opportunity. Big data technology and analytics were starting to emerge as high growth areas, so we wanted to leverage these trends to serve the global life sciences industry. In my initial years, I worked as Director – focused on New Business Development & Initiatives driving service line strategy, expansion and innovation. I then took over the reins of the company as CEO in 2016.
Prior to joining Excelra, I held key leadership positions at a renewable energy start-up where I focused on business development, capitalization, growth & scaling; and prior to that I was at GE Capital in the Energy Financial Services business. I hold an MBA from INSEAD and a BA in Economics and International Relations from Tufts University in Massachusetts.
Question: What was the initial vision behind the launch of Excelra and how would you say that vision has changed?
Anandbir: Excelra was created with the purpose of transforming life science data into actionable insights for our R&D clients. A two-pronged approach is used to achieve this. First, structuring and unifying the data from disparate sources into analysis-ready scientific datasets, and second, employing high-end data analytics to build predictive models for unlocking insights to accelerate drug research and development.
The original vision that started the company has undergone some evolution. Firstly, the analytics team has graduated into a high-end data science team. Secondly, we have made strong forays into clinical pharmacology and value evidence areas. Thirdly, across Excelra we have created a foundation of a rapidly growing R&D BIO-IT team which itself has expanded from a support function to a flourishing independent business unit. This evolution into specific domains and leveraging pure tech has been due to high customer demand.
Excelra’s vision today is to be a data structuring, analytics and engineering/data science partner, empowering innovation in the global life sciences industry. Our offerings run from discovery to market, essentially catering to the entire pharma R&D value chain.
Question: What would you say sets Excelra apart from your competitors?
Anandbir: The Excelra edge comes from a seamless unification of data, deep domain expertise and data engineering. We have put together ‘bilingual resources’ who have a blend of science + technology. These resources are very hard to find, and through various training programs, a wide variety of projects and experience, we have been able to cultivate a team that is versatile in skill and agile in practice. Our people were, are, and will remain our biggest asset!
Further, Excelra has deep experience and trusted relationships in the pharma industry, with some dating back to nearly two decades (such as GVK Informatics). These long-standing relationships have helped develop an image of being less of a vendor and more of a trusted ally that is always committed to our clients’ success. Nurturing these relationships itself offers a big competitive advantage.
Lastly, what defines us is our values and culture. We are obsessed with delivering the highest quality solutions with personal attention to each client’s specific needs while maintaining trust, transparency, and integrity every step along the way. This may sound basic, but we take it to another level!
Question: Can you tell us more about who your clients are, and how you work with them?
Anandbir: Excelra is the preferred data and analytics partner to over 90 global biopharma companies, including 17 of the top 20 pharmaceutical companies in the world and some of the leading drug discovery focused AI companies. We have multiple business models that include providing high end consulting services for specific objectives or providing highly skilled resources as an extension to the partner’s teams. We also offer subscription products and platforms, as well as long term data and technology partnerships.
Question: What are the most notable client success stories?
Anandbir: There are many, but two recent examples come to mind.
Excelra teamed up with one of the fastest growing clinical stage biotech companies that was creating an internal bioinformatics services function. Excelra provided critical, multi-skilled resources to act as an extended team to the client, so they could hit the ground running. It’s been 2 years since the relationship began and the team so far has delivered ~10 diverse projects ranging from response predictive models, standard bioinformatics analysis for drug treated data, project metadata management, to OMICs pipeline development. This analytics support was fundamental in helping their lead candidate to transition into the clinical phase with a very robust recruitment and stratification strategy.
Another success story is with a large top 10 pharma company for whom we have been providing high-fidelity curated clinical trial datasets for the last few years. Impressed by the quality and turnaround time of service delivery as well as our responsive engagement model, we have recently been made their dedicated data partner to deliver curation services across all indications in their clinical pipeline! We have become a seamless extended arm of their global statistical sciences and advanced analytics groups.
These datasets are carefully extracted and normalized into analysis-ready datasets for Model-Based Meta-Analysis (MBMA), QSP and other statistical models. Through these applications, our client gains valuable intelligence into a clinical program’s competitive landscape and comparative effectiveness. They can benchmark dose-response, time-course, placebo effects, and outcome heterogeneity for a given drug class and indication. The insights gained are used to optimize clinical trial designs and marketing/commercial strategies among other use cases.
Question: What do you think is the greatest opportunity for pharma to improve the speed and efficiency of discovering and developing new therapies?
Anandbir: McKinsey estimates the size of the digital opportunity in life sciences to be $50–150 billion of EBITDA across the industry, and BCG analysis reckons that a data science driven re-engineering of the pharma value chain can unlock ~2X economic value.
However, Pharma has been relatively late in embracing the data and digital revolution compared to other industries such as retail, media, financial services and transportation. One key reason is the siloed nature of R&D and the traditional regulatory caution that drives the mindset. There is also a bit of cultural reluctance in perceiving data as an asset to be leveraged, rather than an output to be guarded.
Having said that – these barriers are rapidly breaking down and there is a real momentum shift across the industry to adopt the latest data and digital initiatives across R&D. Most large pharma companies now have a ‘CDO’ function driving a range of use cases such as: predictive modelling & AI for drug discovery; smart clinical trial design, biomarkers for patient stratification, RWE driven clinical trial feasibility & patient recruitment, ‘Beyond the pill’ approaches using wearables, mobile apps for digital patient engagement etc. The Covid-19 pandemic has only accelerated all these trends.
Question: The pharma business model is under significant strain at the moment, with the average cost of getting a drug to market doubling every 9 years. How can Excelra help with this?
Anandbir: Every aspect of the pharmaceutical value-chain involves generation of voluminous data. Excelra turns these vast data-pools into meaningful insights that unlock operational efficiencies, and increase the speed and accuracy of drug discovery, clinical development, regulatory approval, reimbursement, and market access.
To take a case study in point, Excelra has meticulously curated and structured valuable proprietary datasets. One such intelligence platform is GOSTAR®, the largest Structure Activity Relationship (SAR) database for drug discovery. Our scientists have curated a 360° view of close to 8 million small molecule drug compounds and more than 23 million SAR property data points! From target profiling to hit identification and lead optimization, GOSTAR® is a critical resource for medicinal and computational chemists capturing granular assay data across chemical, biological, pharmacological and therapeutic dimensions. Some of the top AI drug discovery biotech companies train their algorithms on GOSTAR® data. Similarly, we offer a range of data products and services including – translational biomarkers (GOBIOM), clinical trial design/outcomes and real-world data. With the likes of GOSTAR® and other data assets, Excelra is providing scientists a starting point by offering deeper insights and accuracy which in turn helps shorten that 9-year window.
On the other hand, as a scientific consultancy, we partner with companies in data science driven drug discovery, target and biomarker identification and validation. We help them in bioinformatics, drug repurposing, indication prioritization and drug combination prediction. Once the molecules hit Phase II in clinical development, we help generate and communicate the value and evidence of the molecule through pharmacoeconomic modelling, value communication reimbursement and RWE analytics. Again, all these consulting services help in either progressing a faster clinical program or getting the “Phase IV” approval in a shorter timeframe.
Finally, as a data engineering and technology partner, we provide expertise in semantic enrichment, ontology mapping, data harmonization, data ingestion pipelines, meta/master data management, semantic and knowledge graph solutions; as well as solving life science R&D technology needs in application development, workflow and process integration and data visualization.
All these offerings help shorten the time to market, either fail fast/fail early or help get to the market quicker. Ultimately, it’s a collaborative approach with our clients to prioritize areas of the most critical need where Excelra can bring a holistic approach combining data, analytics and technology.
Question: How have you noticed perspectives and engagement levels changing over the last few years, with respect to adoption of more data-driven approached for discovery and development?
Anandbir: As I mentioned earlier, we have noticed a distinct uptake in the interest and appetite for data-driven approaches both at a functional level as well as at an enterprise level. Especially in the Covid-19 environment, our relationships have seen a deeper level of engagement, increased budgets and demand for outsourced digital solutions.
Question: What would you say is the single biggest untapped opportunity for pharma companies to improve the effectiveness and outcomes from their R&D programs?
Anandbir: The interlinking between the world of drug research and R&D (Pharma) and clinical practice (Healthcare) is best exemplified by Real World Evidence (RWE), which has the potential to enhance the efficiency of drug development and provide new evidence on risks and benefits of medical products. While there has been a lot of development in this area, there remains an untapped potential to maximize the use of RWE.
It is still a big challenge to connect the dots and stitch together a full longitudinal picture of a patient’s experience. If ongoing clinical practice can generate regulatory grade data, this can transform the way clinical trials are conducted in the future. There’s still a long way to go but we are on the way and we will get there.
Question: You’ve recently released some open access resources to support scientific efforts to combat COVID-19. Can you tell us more about those resources?
Anandbir: That’s right. We have launched a biomarker database and a drug repurposing database related to Covid-19: Excelra’s Covid-19 Resource Hub.
The biomarker database is excerpted from our biomarker intelligence platform – GOBIOM. The database is a compilation of manually curated biomarkers from published clinical trials, evaluating potential drugs or biologics for the treatment of SARS-CoV-2. The database additionally includes information on FDA-NIH recommended BEST classification of biomarkers, supported with direct links to referenced literature.
The drug repurposing database is a compilation of ‘Approved’ small molecules and biologics, which can rapidly enter either Phase 2 or 3, or may even be used directly in clinical settings against Covid-19. The database additionally includes information on promising drug candidates that are in various ‘clinical, pre-clinical and experimental’ stages of drug discovery and development. Supported with referenced literature, we provide mechanistic insights into SARS-CoV-2 biology and disease pathophysiology.
Both the databases are provided as ‘Open Access’ resources to the research community – it’s a small contribution to the global efforts towards finding a medical breakthrough against Covid-19.
