Driving Value in Biopharma R&D through Digital Transformation

Contributed Commentary by Ashu Singhal, Benchling

February 4, 2022 | Accomplishments in biotech that once seemed impossible are being achieved with extraordinary efficiency. The COVID-19 pandemic has only intensified the urgency of speed-to-innovation in biotech to save lives around the world. Biotech leaders recognize the importance of increased efficiency in drug development, and consequently, R&D leaders will push their teams to continue developing at this pace.

Rapid scientific innovation is dependent on streamlining three key capabilities: improving data usability, enabling global cross-team collaboration, and automating scientific workflows. We believe that digital technologies should serve as the foundation that connects your data, people, and processes together to drive scientific discovery. From our perspective, the companies that embrace digital will ultimately win the R&D race.

The majority of biotech leaders agree. According to a recent survey of 250 pharmaceutical executives, 72% believe that digital transformation is critical to achieving R&D imperatives. However, most companies are not approaching digital transformation strategically. An incremental approach has resulted in 88% of digitalization to happen in silos rather than at-scale across groups within the organization. The lack of a cohesive approach has also made it difficult to measure the business value delivered to the company — as reported by 60% of respondents. Yet measurement is critical for showcasing that you have deployed meaningful technologies, and building a case for their continued investment.

This leads to the question: How can biotech organizations execute on successful digital transformation?

I believe success requires focus in three areas: detailed self-assessment, cohesive digital deployment, and a commitment to measuring business value.

Assess Your Current Digital Maturity

To begin, you must outline your current approaches to data governance, collaboration, and workflow optimization, including the role that digital technologies play (if at all), and understand the limitations and barriers you face today.

This starts with asking questions about your current systems. How many disparate solutions do you use for data management? How integrated are these to support automated data capture, data search, and access? How easy is it to update the data model without downtime to day-to-day operations?

Many R&D leaders stop here, but that is incomplete. It is important to consider the capabilities afforded by tech solutions that go beyond the data and ensure the digital tools are fully embedded across the organization. Are the tools intuitive to promote adoption? How efficiently are your teams able to collaborate? Can your data be mobilized to drive scientific and operational insights? Is lab instrumentation being used optimally to automate workflows?

Once you establish a baseline understanding of your current level of maturity and define your limitations, you can outline future goals. Be honest in your assessment, and prioritize the areas where you are furthest behind to ensure you are up-leveling your R&D where it is most needed and to see the greatest business impact. Holistically evaluate and deploy digital technologies that not only meet immediate needs, but also maintain existing efficiencies while enabling long-term scale and growth with the organization.

Measure Success and Business Impact

Deploying a new technology is not enough. Biopharma leaders need to measure success in order to justify the continued investment and change management required for long-term adoption and support. Ultimately, digital tools are brought in to bring about meaningful change — this needs to be proven to internal stakeholders. However, most leaders are struggling to measure the success of digitalization. There simply hasn’t been a framework or methodology in place for such an evaluation.

Measuring business value begins with defining meaningful value metrics based on the previously outlined current state limitations. It is vital to quantify value before and after adoption of your digital tool through surveys and interviews with business and research colleagues, and rigorous internal analysis of operations and performance data.

Once you’ve recognized the challenges your organization is facing, you can measure the impact of digital transformation. Some metrics to consider may include:

• Have digital tools impacted the ability to access and use high quality data to drive scientific insights and decision-making?
• To what extent have new technologies directly improved productivity in the areas of data capture, search, and compilation?
• How significantly has digital supported the efficiency and speed of scientific workflows — and by how much?

Improvement along these metrics can lead to tangible value. Each workday will become easier and more productive for scientists as they complete day-to-day tasks with more efficiency. Having access to the entirety of data allows them to make smarter decisions, expedite workflows, and get novel treatments to patients more quickly. Additionally, some of these metrics can be tracked and converted to ROI, which in turn will help with business justification and continued investment.

I have seen biotech companies who implemented a cohesive digital solution experience success in many forms, including these examples:

• ~95% of end users reported that a single unified system benefitted the ability to find and use data, compared to prior disparate systems.
• Scientists saved ~8-10 hours of time per week on low-value data management tasks to re-allocate to higher-order activities like experimental design and analysis.
• A core antibody discovery workflow was accelerated by ~9 business days due to improved data search, access, and hand-offs, helping expedite drug development.

Continue to track success as the digital solution is progressively adopted by additional teams across the organization. This exercise will enable you to understand if the digital solution is providing value to your business.

Modern digital technologies serve as a key means to connect data, people, and processes together. These solutions provide scientists with the critical ability to centralize, standardize, access, and use data in ways that make it more powerful than ever before. Once equipped with this, teams can work together to streamline workflows and leaders can make necessary pipeline decisions.

In order to leverage digital to achieve these capabilities, it is necessary to map out your current digital maturity and formulate a cohesive strategy. Ultimately, the right tools should deliver meaningful business value and support your organization in bringing about rapid scientific innovation to save lives.

Ashu Singhal is President and co-founder of Benchling, pioneer of the R&D Cloud powering the biotechnology industry. Today, more than 200,000 scientists at over 600 companies and 7,000 research institutions globally have adopted Benchling's R&D Cloud to make breakthrough discoveries and bring the next generation of medicines, food, and materials to market faster than ever before. As President and co-founder, Ashu is responsible for leading product development and strategy, helping scientists increase their productivity, collaborate more effectively, and reach new data-driven insights. Before Benchling, Ashu studied computer science and computational biology at MIT and co-founded a social media analytics company that was acquired by Twitter. Ashu can be reached at ashu@benchling.com.