Bench to Business

Notes and reflections from the space between science and business — the messy, fascinating early stages of biotech

πŸ§ͺ When the Medicinal Chemistry Lens brings instant clarity

In early drug discovery, some situations feel ambiguous until you look at them through the medicinal chemistry lens!
An experienced medicinal chemist doesn’t just optimize potency or run SAR cycles, we understand the biological environment the molecule must navigate from the moment it enters the body to the moment it reaches its target.

πŸ‘‰ Drug–Target Interaction: 3D binding pose and selectivity across isoforms
πŸ‘‰ Physiological Barriers: gut absorption, brain penetration, cellular and nuclear membranes, transporter systems
πŸ‘‰ Elimination Pathways: liver oxidative and conjugative metabolism, cellular and plasma metabolic enzymes
πŸ‘‰ Behaviour across Biological Compartments: plasma protein binding, volume of distribution, tissue exposure
πŸ‘‰ Key Toxicity Signals: drug–drug interactions, hERG, genotoxicity, mutagenicity

Apply the medicinal chemistry lens, and complexity resolves into strategy: the science aligns, and the project advances with purpose.

🧬 The Slide 7 — the moment a great pitch gets lost in too much data

let’s talk about a familiar scene in biotech pitches, the one I like to call “Slide 7.”
That moment when a clear, promising presentation suddenly turns into a flood of in vitro data for too many compounds. And just like that, attention starts to drift.

Sharing results — ICβ‚…β‚€, selectivity, PK, in vivo efficacy — is essential; that’s what builds scientific credibility. Still, the strongest pitches often stand out by focusing the story:
πŸ‘‰ highlighting the lead compound,
πŸ‘‰ profiling it with clarity,
πŸ‘‰ noting the strength of back-ups analogs within the same chemical series.


A good pitch doesn’t try to show everything — it shows just enough to spark interest. 

πŸ§ͺ The “minimum viable data” in early-stage drug discovery

A common challenge for early-stage biotech founders: knowing which data – and when – to show investors. It’s rarely about volume, but about relevance.
- Too little, and the project feels fragile
- Too much, and you burn resources before you even fundraise


Investors usually look for a few clear signals of potential:
πŸ‘‰ credible target validation
πŸ‘‰reproducible biological effect
πŸ‘‰a development plan that shows the next critical milestone


That’s where science turns into strategy — deciding what to share, when, and why.