Magazine Article | January 31, 2020

Artificial Intelligence: The Accelerating Force For Life Sciences Startups

Source: Life Science Leader

By Peter Meath

Nearly every day we see news of innovative startups raising investor funds based on emerging technologies, specifically artificial intelligence (AI). Investment in AI-focused startups by VCs has soared sixfold since 2000, according to Stanford University’s AI Index.

As the healthcare landscape evolves to a value-based system, and stakeholders become more demanding, life sciences startups seek to embrace AI and data analytics to demonstrate value and provide better outcomes. These emerging trends are quickly becoming fundamental elements of business strategy for many life sciences startups. Becoming a lasting AI-powered startup in the space requires strong financial backing to recruit top data scientists, improve technologies, scale up, and eventually achieve widespread adoption. Innovators need to establish their product-market fit, plan ahead for funding, and utilize strategic business development approaches to cultivate growth.

AI IN ACTION

Many life sciences startups perceive the application of AI to their business as a massive undertaking, involving full-scale organizational transformation. However, the best way to capitalize on AI’s potential is to start small, with highly targeted use cases.

The Case For Med Tech

AI can help med tech save lives by increasing diagnostic accuracy, surgical precision, and patient management.

  • Diagnostic Accuracy: AI’s use in diagnostics is already benefiting patients by helping to identify diseases more accurately. This is a substantial advancement, as diagnostic errors can lead to significant patient complications.
  • Surgical Precision: The operating room is finding value in AI, utilizing it to improve surgical outcomes. By offering real-time data insights, AI provides the visibility and accuracy to help surgeons improve their movements throughout procedures and determine follow-up analysis.
  • Real-Time Patient Health Management: Our lives today revolve around our smartphones, and the extensive amount of personal data already being collected via our smartphones can benefit patients and doctors by helping to virtually manage health while reducing costs through telemedicine (data privacy still should be a concern).

The Case For Clinical Trials

AI-powered tools can help solve many of the obstacles preventing effective clinical trials because of their potential to analyze patients’ electronic medical records anonymously, quickly cross-referencing hundreds of available trials based on specific criteria. The ability to reference and deduce from this massive data set in real time is manually unattainable for busy medical teams. AI can use the data from these records to better identify probable fits for clinical trials, leading to improved protocols and patient recruitment/retention numbers, more accurate time estimates, and lower costs. AI also can increase trial success rates by finding patterns across symptom progression and outcomes.

The Case For Drug Discovery

AI can speed up drug discovery by optimizing workflow. Automating data management and streamlining the labor-intensive, data-heavy process of drug development lead to more targeted results. Integrating data with workflow management to improve efficiency ultimately reduces the cost of drug discovery.

AI holds the promise of reforming the life sciences industry, which is well-positioned to benefit from the potential of unveiling new insights from a world of unstructured data. However, AI is still in its infancy, and startups will have to remain flexible and adaptive as the space continues to evolve.

THE FUND PART

Beyond successful technical strategy and product-market fit, growing a life sciences startup involves funding. Determining the ideal source of capital to help fund growth can be difficult — but it also can lead to greater long-term success. Life sciences startups have many channels available to raise capital at various stages, each with their own advantages and concerns to contemplate. Founders must understand which asset class will strategically address their unique needs and support their success, while also realizing that their funding needs will change at each growth stage.

  • Incubators or accelerators can be a good option for early-stage startups. Many can provide incredible facilities for much less than the cost of building your own state-of-the-art laboratory. The key factors when determining which incubator is right for you include the occupancy term options, subvertical specialties, resource needs, and quantifiable costs.
  • Family offices are becoming more active in the life sciences landscape. For a startup seeking capital, a key advantage of working with a family office is the lack of constraints. Without board representation or control, family offices are more agile in investment management, which makes them a natural fit for early-stage funding.
  • Venture firms can be an optimal fit for startups at every stage of development, serving as a strong source of insight to help founders navigate opportunities and threats throughout the preclinical, clinical, and commercial trial stages.
  • Corporate investors typically invest directly in startups to foster technological development. While they often have the goal of eventual merger or acquisition, they may also pursue investments for pure ROI or competitive advancement, making corporate venture capital a suitable avenue for many growing startups.
  • Crowdfunding is particularly beneficial for life science startups with a strong emotional tie-in, as backers do not have any financial returns tied in with their contributions. This option could work well for a patient-focused cancer care mobile platform, for instance, rather than a lab-based clinical analytics software.

STRATEGIC APPROACHES TO GET AHEAD

  • International Expansion: Increasingly, life sciences startups are considering international expansion at earlier stages of the business life cycle to tap into new markets, gain access to innovation and technology, better serve local needs through global operations, and increase cost savings. It is also pragmatic to think strategically about the different value that a startup’s products and solutions may hold in different regions when developing an expansion plan.
  • Balance Agility and Scalability: Building momentum for an innovative life sciences solution often involves the need to scale up, but maintaining the agility that defines a startup is crucial to scaling successfully in this industry. In a dynamic, evolving market where life sciences companies are increasingly investing in development and the manufacturing chain, how do these companies remain nimble and proactive when opportunities to expand the scope of the business present themselves? Utilizing the latest technological advances in development, design, and manufacturing, while also investing in key talent that can help maximize the investment in these technologies, can help companies remain agile and in front of a changing market landscape — attributes that are vital to long-term sustainable growth.
  • Diversify Offerings: Founders should carefully contemplate their asset diversification strategies as they evolve their business. Benefits to diversification include having multiple opportunities to succeed in a given market by spreading the startup’s core technological advantages across different applications. This also helps with the financing landscape and with risk mitigation in a clinical setting, as success or failure is not beholden to one individual pathway. A well-diversified company can sensibly evaluate results and terminate weaker solutions, while building out optimal paths to market.

HIGH STAKES FOR HIGH RETURN?

AI has the potential to revolutionize the life sciences industry if startups take a calculated approach to providing solutions and move forward with a strong strategic plan for funding, development, and growth. To achieve the biggest impact, life sciences startups will need to invest in a highly trained team, including a panel of experts from financial institutions, data science experts, legal compliance organizations, and insurance companies with expertise in this fast-growing industry.

PETER MEATH is managing director and co-head of healthcare and life sciences in J.P. Morgan’s Commercial Bank.