The Nonclinical Podcast

Most nonclinical teams treat study design as a logistics question — pick a species, pick a route, hand it to the CRO. That's protocol development. Real study design answers a different question: what does this study need to deliver, and is the design actually capable of delivering it? In this episode, we break down the three things every study design has to align with, and the four signals that a design is in trouble before the study even starts.

Key takeaways:

• There's a critical difference between protocol development (logistics) and study design (strategy) — and most teams skip the second one entirely
• Every study design has to align three things: regulatory expectations, the scientific question, and program timeline. Miss one and the study won't serve the program
• A study designed only to meet ICH guidance is technically defensible and often scientifically useless
• The four warning signs: dose justification reads like a calculation not a rationale, endpoints are a standard battery not a curated set, recovery groups are included or excluded by cost not by design, and there's no interpretation plan before the study runs
• Before approving any protocol, ask one question: is this design actually capable of delivering what the program needs?

Links:

• The Complete Guide to Nonclinical Development — Module 4: Study Design: https://nonclinical.academy/
• Work with Dessi: dessiturner.com
• Read the full newsletter issue on LinkedIn: https://the-nonclinical.com/

The Nonclinical is hosted by Dessi McEntee, MS, DABT — board-certified toxicologist and Fractional Head of Toxicology. Subscribe to the newsletter on LinkedIn, take the course at nonclinical.academy, or work with Dessi at toxistrategy.com.

The word "adverse" appears in your study report and the room goes quiet. Most founders treat it like a verdict. It isn't. It's a scientific conclusion — and it's one you need to own, understand, and be ready to defend when FDA asks about it. In this episode, we walk through the five-question framework for evaluating any toxicology finding, and explain the difference between a finding that limits your program and a finding that doesn't.

Key takeaways:

• "Adverse" is not a label your CRO assigns and walks away from — it's a scientific starting point that requires your interpretation and defense
• An elevated liver enzyme at the high dose might be adverse, or it might be an adaptive response — and that distinction directly determines your NOAEL and safety margin
• The five questions: Is there a dose response? Is it reversible? Does histopath confirm it? Is the magnitude biologically significant? Is it consistent across sexes and species?
• A non-adverse call requires just as much documented rigor as an adverse finding — "we don't think it's adverse" is not a regulatory argument
• An adverse finding doesn't kill your program. An adverse finding with no interpretation, no context, and no safety argument does

Links:

• The Complete Guide to Nonclinical Development: https://www.nonclinical.academy/
• Work with Dessi: dessimcentee.com
• Subscribe to the newsletter: https://the-nonclinical.com/

The Nonclinical is hosted by Dessi McEntee, MS, DABT — board-certified toxicologist and Fractional Head of Toxicology. Subscribe to the newsletter on LinkedIn, take the course at nonclinical.academy, or work with Dessi at toxistrategy.com.

You walked an investor through your toxicology data. Species rationale, dose-response, NOAEL, safety margins — technically airtight. They nodded. Then they turned to your CEO and asked: "So can the drug actually be given to people?" That gap isn't a science problem. It's a translation problem. In this episode, we break down the five places nonclinical scientists lose investors — and exactly how to reframe the same data so it answers the questions investors are actually asking.

Key takeaways:

• Investors aren't reading your nonclinical package for scientific defensibility — they're reading for what could kill the program
• The same NOAEL means two different things depending on the reader: to FDA it's a dose justification floor, to an investor it's the answer to "how much room do you have before this gets dangerous?"
• Species selection isn't regulatory boilerplate — it's proof that if the drug behaves badly, you'll see it in animals before it touches a patient
• "Characterized and bounded" is the most powerful phrase in a pitch room — it tells investors you found the monster, measured it, and put it in a cage
• The pre-IND meeting is your trump card with investors and most founders bury it on slide 14 — lead with it instead
• Defensiveness in a pitch signals risk. Walk in knowing you and the investor have the same job: finding every way this program could fail

Links:

• The Complete Guide to Nonclinical Development: https://www.nonclinical.academy/
• Work with Dessi: toxistrategy.com
• Read the full newsletter issue on LinkedIn: the-nonclinical.com

The Nonclinical is hosted by Dessi McEntee, MS, DABT — board-certified toxicologist and Fractional Head of Toxicology. Subscribe to the newsletter on LinkedIn, take the course at nonclinical.academy, or work with Dessi at toxistrategy.com.

Every animal survived. Body weights stable. No major clinical signs. You're practically popping champagne — and you're about to get an FDA hold. Because buried in the appendices is a TK table that proves your drug never actually made it into the bloodstream. In this episode, we break down toxicokinetics — what it is, why it underpins every dose justification you'll ever make, and what good, bad, and ugly TK profiles actually look like in practice.

Key takeaways:

• TK is just pharmacokinetics in the context of a toxicology study — Cmax, Tmax, AUC, and T½ are the bridge between the dose you give and the effects you see
• Good TK tells a clean, cohesive story: consistent exposure, dose-proportional increases, well-timed sampling — it validates your NOAEL and supports your IND
• Bad TK doesn't fall apart completely, but introduces enough uncertainty to make interpretation tricky — inconsistent exposure, non-linear AUC increases, and exposure overlap between dose groups
• Ugly TK undermines the entire study — no systemic exposure at high dose, formulation failure, unexpected accumulation — and can force you to repeat the study entirely
• TK is not a supporting actor. It's part of the main story. Review it alongside findings, not as an afterthought

Links:

• Early access — The Complete Guide to Nonclinical Development: https://www.nonclinical.academy/

The Nonclinical is hosted by Dessi McEntee, MS, DABT — board-certified toxicologist and Fractional Head of Toxicology. Subscribe to the newsletter on LinkedIn, take the course at nonclinical.academy, or work with Dessi at toxistrategy.com.

Your IND is rejected before a single human being ever reads it. Not because the science is wrong — because a 10-year-old legacy file was missing a digital tag. In this episode, we break down exactly what goes into the nonclinical sections of an IND, how the 5-module eCTD structure works, and the SEND dataset rules that silently kill submissions before they ever reach a reviewer.

Key takeaways:

• The IND is organized into 5 modules — and the nonclinical program lives primarily in Module 2 (summaries) and Module 4 (study reports and SEND datasets)
• Module 2.4 (Nonclinical Overview) is written last — after the detailed 2.6 summaries are complete — because it summarizes them
• Every toxicology study listed in Module 2 must have an associated study report in Module 4, and vice versa — no orphans allowed
• SEND datasets are required for almost all tox studies, including nonGLP studies — and a missing SEND dataset triggers automatic rejection before a human reviewer ever sees your data
• Even studies run 10 years ago still need at minimum a TS domain to pass validation — age of the study is not an exemption

Links:

• My course: The Complete Guide to Nonclinical Development, https://www.nonclinical.academy/
• Work with Dessi: toxistrategy.com
• Read the full newsletter issue on LinkedIn: https://the-nonclinical.com/

The Nonclinical is hosted by Dessi McEntee, MS, DABT — board-certified toxicologist and Fractional Head of Toxicology. Subscribe to the newsletter on LinkedIn, take the course at nonclinical.academy, or work with Dessi at toxistrategy.com.

Everyone in drug development is talking about New Approach Methodologies — AI, organ-on-a-chip, virtual control animals, in silico modeling. The vision is compelling: fewer animals, faster timelines, better translational data. But where are we actually? In this episode, we cut through the hype and take an honest look at where NAMs stand in nonclinical toxicology today, why the hardest part of the pipeline has been the slowest to change, and what it would actually take to get there.

Key takeaways:

• NAMs are advancing rapidly on either side of nonclinical safety — ADME, in vitro screening, computational modeling — but the GLP tox studies that actually get you to IND have been the slowest to change
• The reason is structural: IND-enabling tox studies are the most expensive, most time-sensitive, and most risk-laden studies in the program — most companies won't experiment there
• The silo problem is real: regulatory safety decisions are made by comparing data within a single study, which makes integrating external datasets architecturally difficult
• Virtual control animals (Charles River/Sanofi) are one of the only dedicated computational solutions in nonclinical toxicology — and may be proof of concept for what's possible
• The FDA is moving in the right direction on NAMs — but most toxicologists would not submit a full IND without GLP animal studies today, and that's not a failure of imagination, it's a responsibility to patients

Links:

• Check out my course: https://www.nonclinical.academy/
• Data Is Not Strategy on Amazon: https://a.co/d/02xUsV6K
• Work with Dessi: toxistrategy.com

The Nonclinical is hosted by Dessi McEntee, MS, DABT — board-certified toxicologist and Fractional Head of Toxicology. Subscribe to the newsletter on LinkedIn, take the course at nonclinical.academy, or work with Dessi at toxistrategy.com.

More data should mean less risk. In nonclinical development, that's not always true. In this episode, we explore the concept of data hormesis — the inflection point where accumulating more data stops reducing uncertainty and starts creating it. If your team is running another study because the last one didn't give you the answer you needed, this episode is for you.

Key takeaways:

• Data hormesis is the point where more information stops helping and starts obscuring the path forward — just like a drug that's beneficial at low doses and toxic at high ones
• Early in development, data reduce uncertainty. Beyond a certain point, signals compete for attention rather than converging toward resolution
• When decisions aren't defined early, data accumulation quietly becomes a substitute for judgment rather than a tool to support it
• The patterns are recognizable: equivocal findings trigger rework instead of interpretation, borderline results lead to more studies without clarity on what would actually change
• Programs that move efficiently to IND aren't the ones with the most data — they're the ones that decided early which risks are acceptable and which questions are worth answering now
• Data don't create strategy. They make strategy visible.

Links:

• Data Is Not Strategy on Amazon: https://a.co/d/02xUsV6K
• Work with Dessi: www.toxistrategy.com

The Nonclinical is hosted by Dessi McEntee, MS, DABT — board-certified toxicologist and Fractional Head of Toxicology. Subscribe to the newsletter on LinkedIn, take the course at nonclinical.academy, or work with Dessi at toxistrategy.com.

"No major findings." Three words that instantly lower the blood pressure of every executive in the room — and sometimes, quietly derail a program. In this episode, we unpack why a clean toxicology study can still leave your IND dangerously exposed, what teams consistently get wrong when they see no major findings, and why the absence of a finding is never the end of interpretation — it's where interpretation has to begin.

Key takeaways:

• "No major findings" describes what was not observed — it is not an interpretation of what the study resolved
• A clean study still leaves critical questions open: how close was exposure to the clinical range? What assumptions are now baked in about escalation?
• Once "no major findings" enters the conversation, behavior changes — dose rationales harden, exposure assumptions stop being tested, follow-on studies are designed from reassurance instead of uncertainty
• The consequence doesn't show up in nonclinical — it shows up at IND when you're asked to justify decisions you thought were already made
• Strong programs use clean studies as an opportunity to do more thinking, not less — documenting assumptions, defining boundaries, and stating explicitly what would change the program's direction

Links:

• Data Is Not Strategy on Amazon: https://a.co/d/02xUsV6K
• Work with Dessi: https://www.toxistrategy.com/

The Nonclinical is hosted by Dessi McEntee, MS, DABT — board-certified toxicologist and Fractional Head of Toxicology. Subscribe to the newsletter on LinkedIn, take the course at nonclinical.academy, or work with Dessi at toxistrategy.com.

"Our CRO has QA — we're covered." It's one of the most common phrases in biotech, and one of the most dangerous assumptions in nonclinical development. In this episode, we break down the critical difference between CRO QA and sponsor-side oversight, why GLP compliance and regulatory strategy are two completely different things, and what happens when nobody is doing the sponsor's job.

Key takeaways:

• CRO QA ensures the CRO complies with GLP — that's it. It does not ensure your study design supports your regulatory strategy
• When a protocol deviation occurs, CRO QA documents it perfectly — but nobody assesses whether it invalidates your NOAEL or affects your IND
• Big Pharma has five layers of oversight. Most biotechs have two and hope that's enough — the missing layer is sponsor-side QA
• Real-time study monitoring with a regulatory lens is what catches problems when you can still fix them, not six months later in the final report
• Most biotechs choose to do nothing by default — not because they've evaluated the risk, but because they don't know the gap exists

Links:

• Data Is Not Strategy on Amazon: https://a.co/d/02xUsV6K
• Work with Dessi: www.toxistrategy.com 

The Nonclinical is hosted by Dessi McEntee, MS, DABT — board-certified toxicologist and Fractional Head of Toxicology. Subscribe to the newsletter on LinkedIn, take the course at nonclinical.academy, or work with Dessi at toxistrategy.com.

Most nonclinical teams spend a lot of time thinking about which studies to run. Almost none spend enough time thinking about when. In this episode, we unpack why study sequencing is one of the most consequential — and most consistently underestimated — decisions in IND-enabling development, and walk through the three sequencing mistakes that quietly accumulate risk while looking like efficiency.

Key takeaways:

• Sequencing is an informational problem, not a scheduling problem — and confusing the two is where programs get into trouble
• Running a GLP pivotal study before dose range is genuinely established is the most common and most costly sequencing mistake
• A clean NOAEL without any adverse effects at the high dose isn't a win — it's a failure to toxicologically characterize your margins
• Parallel execution without informational overlap isn't a compressed timeline — it's two separate bets running simultaneously with limited ability to course-correct
• Regulators aren't just evaluating what your data shows — they're evaluating whether your program was designed to answer the right questions in the right order

Links:

• Data Is Not Strategy on Amazon: https://a.co/d/0cDYM8vP

The Nonclinical is hosted by Dessi McEntee, MS, DABT — board-certified toxicologist and Fractional Head of Toxicology. Subscribe to the newsletter on LinkedIn, take the course at nonclinical.academy, or work with Dessi at toxistrategy.com.