Clearing the Path: How Cornerstone AI is Reshaping Data Dynamics in Life Sciences
Reflecting on my journey into the Real-World Data space (RWD) back in 2016, I recall the popular analogy at the time was "data is the new oil." I saw this firsthand as demand for data from sponsors was significantly more than supply of data (my shorthand way of verifying such a statement is in observing willingness to pay – which was high). The industry witnessed the emergence of many innovative data companies, each striving to unlock access to data - some of which I've been privileged to be a part of.
While challenges persist in life sciences gaining access to data, such as ex-US and in the clinicogenomics arena, I firmly believe the next frontier lies in extracting maximum value from available data. This isn’t meant to diminish the role of RWE companies– they have and will continue to be vital to advancing the space forward, but rather to say the supply issue is materially different than what it was 8 years ago.
Recently, I dug into a report by Komodo Health on the State of Data Mining in Life Sciences, and two key points stuck out to me:
Time Investment: Around 70% of life sciences teams invest six or more months in transforming data into a usable state to derive insights. This extended timeline significantly delays across drug research, development, and delivery, with the average duration across teams standing at 7 months.
Heavy Reliance on Consultants: Approximately half of life sciences teams depend on at least four consultants to assist in integrating disparate datasets into their systems or conducting analyses. More than half (53%) of Clinical Development teams in the largest companies ($1 billion+) admit to leaning on consultants for analysis, with over a quarter (27%) engaging six or more.
It's disheartening to see many life science organizations grappling with the same issues outlined in the Komodo report. I think about one life sciences group who has a backlog of clinicogenomic data worth millions of dollars (already purchased) but not getting analyzed because of cleansing and transformation requirements and relative backlog of the team.
Compounding the issue is the reliance on either costly consultants deploying highly specialized technical resources, including PhDs in Biostatistics, or internal teams comprised of equally skilled technical personnel who get handed this work in additional to responsibilities for conducting important scientific analysis.
During my tenure at Ontada, grappling with this challenge was not only frustrating but also a significant impediment to focusing on initiatives that truly move the needle for the business. I think it's safe to assume these data science or biostatistical experts did not kick off their academic journeys with the intent of spending a substantial portion of their time on data cleansing.
My recent transition to Cornerstone AI stemmed from encountering a team of exceptionally skilled and passionate technical and scientific experts equally frustrated with this status quo. Over the past several years, Cornerstone's shared mission has been to address this challenge head-on.
Our primary focus includes:
Data Quality Assessments (Sponsors, 3rd Parties who serve Sponsors): Informing RWD purchase decisions.
Data Standardization and Cleaning (Sponsors, 3rd Parties who serve Sponsors): Preparing acquired data for analytical use post-purchase.
Data Pipeline Monitoring & Optimization (Data Commercialization Companies): Ensuring data providers consistently deliver quality data, including optimizing volume of commercializable data
Each application above is done faster, more thoroughly, and likely more cost efficient than current methods. For example, we have a sponsor who went from 12 weeks (external consultant) to 2 days (our platform) for Data Quality Assessments in their centralized RWD group.
We firmly believe that access to clean data should be a standard across all companies, enabling them to devote their energies to advancing science for the betterment of patients. In other words, let's allow our highly trained technical and scientific experts to concentrate on endeavors that drive meaningful societal impact.
Cornerstone's vision is to evolve into a trusted and impartial industry utility for data cleaning; I borrowed the “utility” concept from Travis May 's writing.
If you resonate with the challenges above, please don't hesitate to reach out. I am thrilled to be part of the Cornerstone team and eagerly anticipate the journey ahead!!!
