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Shifting Risk Mindsets, from Tech to Bio

  • The biospace is expected to undergo a major mindset shift where pharma and biotech firms reclassify as data science companies.
  • Startups reliant on multiple pilot projects face a "death by a thousand pilots" risk involving scope and timeline creep, potentially extending project duration to two times the originally projected amount.
  • Service providers selling pilots to large pharma companies risk failing to achieve the economics required for a sustainable business unless they transition to developing their own preclinical assets and drugs.
  • Platforms focused on identifying novel targets may struggle to capture value because pharma companies view existing targets as abundant and free.
  • Companies should avoid selling technology to pharma until the latter is convinced, comparing initial resistance to children refusing new foods until acceptance is established.
  • The ultimate goal for many biotech startups is to retain the majority of economic value by developing their own drugs rather than licensing technology.
  • Without specific structuring, the commercialization of a single drug asset may starve the broader platform of resources.
  • LLC structures enabling separate entities for individual drug assets can allow parent companies to replicate the model multiple times by attracting new investors for each asset.
  • Unvalidated platforms carry significant risk, as the entire company's value may depend on a single early-stage asset.
  • Engineering-focused platforms are considered more likely to be generalizable and fundamental compared to single-asset dependent models.
  • The venture community and entrepreneurs will need time to socialize to new legal structures like LLCs.
  • Reimbursement is expected to be the primary entry point for diagnostic companies rather than FDA or CLIA regulations.
  • Self-insured employers may be more motivated to fund diagnostics because patients change jobs less frequently than insurance plans.
  • Insurance companies are creating incentives for backloaded return on investment (ROI), with proposals gaining traction to alter payment models.
  • Pilot projects with insurers or payers offer potential to prove ROI and allow companies to start with the end goal in mind.
  • New biology platforms, such as engineered bacteria, may initially find large research institutions as the only natural buyers before the market expands, following the trajectory of sequencing.
  • Entrepreneurs must identify a "killer experiment" to validate or invalidate an idea within the next six to twelve months.
  • Early-stage screening diagnostics face a challenge where ROI is backloaded by five to ten years, making reimbursement difficult for short-term payers.
  • Investors for bio/tech hybrids require a mix of traditional bio and tech investors to bridge knowledge gaps.
  • The investor syndicate mix is predicted to evolve from hybrid to either traditional bio or tech as companies mature toward late-stage investors.
  • Companies must be fluent in one investment language and functional in the other to successfully bring bioinvestors online in the future.
  • The biggest risk in diagnostics is designing a test without confidence of reimbursement.
  • Pilot projects with large companies often result in payments delayed by two times the projected timeline.
  • Companies relying on free sampling strategies may struggle if they are responsible for producing all samples.
  • The success or failure of the first asset from a platform significantly determines the business's future trajectory.
  • Fundamental biological platforms should be structured to allow separate funding streams for those believing in assets versus those believing in the platform.
  • The long, risky, and time-consuming path to validation in therapeutics creates a temptation to begin with pilot projects.
  • Business development is a strategic advantage for bridging the chasm in early-stage deals with pharma.
  • Failing to fully encumber platforms in deal structures risks limiting a company's future ability to operate independently.
  • The primary challenge for new biology platforms is determining how to reach a fundamental point of proof (POC) through a path of increased proof points.
  • Companies should always design for early adopter POCs as a near-term target rather than waiting for late adopters.
  • Tech investors are generally not set up to bear science risk in the manner that biotech investors are.
  • Companies should continuously plan for future funding rounds, considering both metrics and the evolving mix of investors.