This is Part #1 of a blog series describing how disruptive innovation technologies such as Saama’s Life Science Analytics Cloud is enabling the Pharma industry to bend its clinical development cost curve sharply downwards while bringing cures to patients sooner. Co-authored by Nekzad Shroff, Vice President for Business Consulting and Enablement and Amit Gulwadi, Senior Vice President for Clinical Innovations, this blog explains the overall ROI benefits for a typical trial sponsor.
Clinical development is a complex process with many dependencies and tradeoffs. It typically involves an ecosystem of entities such as biotech and pharmaceutical manufacturers (sponsors) and Clinical Research Organizations (CROs) working together in partnership to conduct clinical trials. Drug development is a long and expensive undertaking which has been rapidly rising in complexity and cost over the past decades. This alarming trend has made many headlines1 in the recent past with regulators, politicians, payers, pharma companies, and patients pushing to find new ways to make clinical development costs sustainable.
Sponsors and CROs today are looking for new ways to improve the efficiency, cost, and reliability of their clinical operations in order to bring drugs to market cheaper and faster2. One of the most promising opportunities that they are pursuing involves harnessing the power of their operations and clinical data for better insight and improved decision making. However, a fundamental industry challenge is that this data is spread across multiple different business entities, geographies, application systems, databases, websites, documents, and spreadsheets. Making decisions today is an inefficient, risky, error prone process based on incomplete information, and clinical stakeholders and decision makers often spend more time wrangling data and spreadsheets rather than managing trial and portfolio execution.
In a 2017 study3 of Sponsors and CROs conducted by Veeva, 100% of CROs report the need to unify data across their clinical operations application systems. The top expected benefits of this unification are faster study execution, cost savings, improved study quality and better visibility into studies. However, this task is not easy to accomplish due to the following challenges:
- Multiple applications hold essential data, and these are not integrated
- Data definitions, granularity and context are not consistent across systems
- Systems are owned by different departments and often provided by different vendors
- Reporting is siloed and restricted to the data in each system
- Much critical data exists outside of databases in forms that are hard to analyze such as various textual document formats, spreadsheets, social media and websites
Saama Technologies is on a mission to exponentially drive down clinical development costs and time over the next decade through technology, AI, and collaborative open innovation across its ecosystem (what we refer to as “Moore’s Law for Pharma”4). In order to address the above challenges, Saama has launched its industry leading Life Science Analytics Cloud (LSAC) platform. LSAC is a cutting-edge suite of analytics applications and technologies which bring together and seamlessly integrate the various sources of data (traditional and unstructured), managed in a modern data environment, with a suite of analytics applications leveraging advanced machine learning, artificial intelligence (ML/AI), and visualization techniques to dramatically improve the speed and quality of insights for decision making. LSAC enables sponsors and CROs to harness the power of integrated data across the clinical development lifecycle in order to achieve faster commercialization and reduced development costs. In order to better understand the size of the benefit opportunity from LSAC, we have worked with our clients and industry leaders to create an estimation model. This model quantifies 2 metrics – cost savings and timeline reduction for a trial.
For the purpose of this estimate, we take a fairly typical example of a Phase 2 or 3 oncology trial of 2 year duration and with 100 sites spread across 10 countries across different geographies with different (typical) cost structures. Using our estimation model across both Planning and Conduct phases of the trial, we are able to project that sponsors would be able to save $1.8M in operational costs of a single trial while reducing the trial duration by 6 months by implementing and leveraging the capabilities of LSAC.
Additionally, we know from industry studies that typical success rates for oncology drugs from Phase 2 through to approval are in the range of 6.7 – 10 %5. Given this, we are able to estimate the average aggregate savings from phase 2 and 3 trials to be conducted in a drug program which would be needed for a single successful drug to be approved. This program level benefit is quantified as $85M in operational cost savings and reducing the time to FDA Submission by 12 months.
However, the largest opportunity for biotech and pharma sponsors is on the revenue side. Consider that bringing a drug to market one year earlier gives sponsors an extra year of peak sales. For a drug with estimated peak sales of $1B, this benefit translates into an additional $1B of peak sales revenue over the drug lifetime!
The opportunity is undeniable. In the current environment when healthcare costs are turning unsustainable, there is a huge untapped opportunity for the pharmaceutical industry to transform itself by leveraging the power of data and analytics. Across the board, the industry and the FDA are reorienting processes and policies towards enabling efficiencies, making better decisions, and scaling the clinical development model towards an age of rapid innovation and insights. Saama is on a mission to institutionalize these changes with our partners and clients through our industry-leading LSAC platform. And we’re just getting started!
Follow along as we describe in further detail in Part #2 how Saama Life Science Analytics Cloud is transforming processes, shortening timelines, and reducing costs in the planning phase of clinical trials.
1. See: FDA: Early Stage Drug Development Costs Trigger Higher Drug Costs: Pharmaceutical Technology journal
2. See: Clinical Development; “A Futuristic View” by Dr. S. Cunningham
3. Source: Veeva 2017 Unified Clinical Operations Survey: Annual CRO Report
4. See: In Search of Pharma’s Moore’s Law by Sagar Anisingaraju
5. Source: Chi Heem Wong, Kien Wei Siah, Andrew W Lo; Estimation of clinical trial success rates and related parameters, Biostatistics
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