Script

Special: Off-target effect (technical foundation)

What BenchSci is Looking For:

• How feasible is this/can our team built it?

  • Implementation plan + easy built

• How big of a problem is this problem/why worth focusing?

  • How oncology market can scale to other problems → long-term vision and timeline
  • How much money or impact made from this solution?
    • Case studies to validate relevance

• Real-world validation (i.e. potential customers we've talked to) + BenchSci fit

• Why our solution is the best solution for this specific problem

  • They're looking for biomarker discoveries. → Biomarker daft design. They're solving a symptom of a bad drug
  • the first part of their solution is looking at predictive and surrogate-endpoint biomarkers based on study's design
    • while most solutions work directly in this area, what we're fundamentally identifying is a potential back design of the drug being tested → way early in clinical validation which is much more prominent root cause of failure for all drugs
    • if we don't understand the drug itself, how can you go about picking correct biomarkers if what you are testing for is invalid/not a good representation of the drug itself → the goal is to demonstrate efficacy and save money from potential failure points across trials
      • if your solution is dependent on study design but study design is flawed, then final outcome will still be the same if not just more cheap
      • ours solution aims to assist study design and power all of these other solutions by providing a strong biological foundation through analyzing target validation, as without this central tenet, a drug's efficacy and pre-determined notion of how it should function will become critical and more accurate for the final trial, leading to higher success rates across all stages of the trial → save more money early on in R&D
      • using intial design of the clinical trial to make it more logistical
      • Save more money if you can identify failure right away + Target validation to save (with the focus of off-target effects)

Target Assessment in Drug Discovery:

• insufficient validation of drug targets at an early stage has been directly linked to clinical failures that are costly and low drug approval rates → found that more effective target validation as well as earlier proof-of-concept studies could reduce attrition in phase II clinical trials by 24%, lowering cost of developing new drugs for novel MoAs by 30%
  • target validation requires greater emphasis in order to facilitate the development of new therapies
• need to look at validating target impact on disease process (in terms of survival), druggability, target-related safety issues, biomarker research, and how severe the unmet medical need in potential patient populations intended to benefit from new drug and commercial potential of new drug if successfully reaches market

Preclinical Target Validation (Source)

High attrition underscores the need for better target validation and biomarkers to avoid selection of the wrong target, the wrong patient population, or the wrong dose. (Source)

"Using these two approaches (better target validation and early POC studies) we have estimated that the p(TS) of Phase II compounds can be increased to approximately 50%. As can be seen in our sensitivity analysis [Fig. 3 in the paper; image below in this notion], reducing Phase II attrition by this much will by itself lower the cost per NME by approximately 30%." (Source)

Buisness side of thing

Timeline of our presentation

• 10 second hook + expanding on how big of a market this is
• 1 minute Diving in to the low hanging fruit problem + market opportunity