Conference Tracks

Find Where Your Story Belongs

Four tracks covering the full biotech lifecycle — from early discovery through regulatory approval. Whether you work at the bench, behind a screen, on the manufacturing floor, or inside a regulatory filing, there's a stage for you.

01

Discovery & Research

This is where it all starts — the lab, the hypothesis, the late nights staring at data that doesn't make sense yet. Track 01 is for the scientists who work at the earliest stages of drug discovery: identifying targets, validating biology, running screens, optimizing leads, and figuring out whether an idea has legs.

We want stories from the bench. The assay that took months to get right. The target everyone else had given up on. The collaboration between biology and chemistry that actually worked. The moment you realized your project was dead — and what happened next.

If you've ever run a 96-well plate at 11pm or argued with a medicinal chemist about SAR, this track is for you.

Suggested Talk Topics

  • The experiment that changed everything — a single result that redirected our entire program
  • How we validated a target nobody believed in — and what it took to convince the skeptics
  • My most expensive lab failure and what I learned from it
  • Transitioning from academia to industry: what I wish I knew on day one
  • The tool or technique that transformed our workflow overnight
  • When the data contradicted our hypothesis — and we listened

Who Should Apply

Bench Scientists Medicinal Chemists Biologists Protein Engineers Assay Developers Screening Scientists Pharmacologists
02

Data, AI & Computational Biology

The code behind the cure. Track 02 is for the people building the computational backbone of modern biotech — the ML engineers training models on messy biological data, the bioinformaticians making sense of multi-omics datasets, and the data scientists trying to bring rigor to a field that often runs on intuition.

We want to hear about what actually works (and what doesn't). The gap between a promising Jupyter notebook and a production system. The politics of deploying AI in an organization that doesn't fully trust it. The dataset nobody cared about that turned out to be the most valuable thing in the company.

If you've ever explained a p-value to a biologist or defended your model's predictions to a skeptical discovery team, this is your track.

Suggested Talk Topics

  • How we deployed ML in our pipeline — reality vs. expectations
  • The dataset everyone ignored turned out to be gold
  • Building data infrastructure for biotech: what works and what's pure pain
  • When the model was right and the biologists were skeptical
  • From Jupyter notebook to production: our journey (and all the things that broke)
  • AI in drug discovery — hype vs. what we actually shipped

Who Should Apply

Bioinformaticians ML/AI Engineers Data Scientists Computational Biologists Cheminformatics Scientists Software Engineers Data Engineers
03

Development & Manufacturing

Milligrams to kilograms. Track 03 is for the people who turn molecules into medicines — the process engineers scaling up reactions, the formulation scientists figuring out how to keep a protein stable, the CMC teams writing the sections of the IND that nobody reads but everyone depends on.

This is the invisible work of drug development. When it goes well, nobody notices. When it goes wrong, the entire program stops. We want stories about what really happens when you move from bench scale to GMP manufacturing — the surprises, the failures, the process optimizations that saved entire timelines.

If you've ever lost sleep over a batch record or explained to a discovery team why their favorite solvent won't work at 2000L, this track is yours.

Suggested Talk Topics

  • The scale-up that went sideways (and how we fixed it)
  • One process optimization that saved us months on our timeline
  • CMC — the unsung hero of drug development
  • Why our first three batches failed GMP review
  • Automation in the lab: what we got right and what we got wrong
  • From bench scale to 2000L: lessons in humility

Who Should Apply

Process Engineers CMC Specialists Formulation Scientists QA/QC Analysts Analytical Scientists Manufacturing Leads Automation Engineers
04

Clinical & Regulatory

IND to approval — and everything in between. Track 04 is for the people who navigate the most complex regulatory landscape in the world: the clinical operations managers running multi-site trials, the regulatory affairs specialists interpreting guidance documents, the medical writers turning science into submission-ready language, and the biostatisticians whose analyses determine whether a drug lives or dies.

We want to hear what the textbooks don't teach. The FDA interaction that went nothing like you expected. The clinical trial that hit enrollment problems nobody anticipated. The safety signal that forced your team to rethink everything. The regulatory difference between the US, EU, and Japan that almost derailed your filing.

If you've ever spent a weekend rewriting a Module 2.5 summary or held your breath waiting for an FDA response letter, this track was built for you.

Suggested Talk Topics

  • Our IND filing: what was most unexpected about the process
  • Working with the FDA — what nobody tells you before your first interaction
  • The clinical trial that didn't go as planned (and what we did about it)
  • How I became a medical writer and why it matters more than people think
  • Navigating regulatory differences across US, EU, and Japan
  • The safety signal that changed our entire program

Who Should Apply

Clinical Operations Regulatory Affairs Medical Writers Pharmacovigilance Biostatisticians Clinical Data Managers Drug Safety

Don't see your role?

If you work in biotech and have a story worth telling, we want to hear it. These tracks are guidelines, not gatekeepers. The best talks often come from people who don't fit neatly into any category.

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