The cardiometabolic field is advancing faster than most early-phase trial frameworks were built to accommodate. That gap — between how quickly the science is moving and how slowly study design adapts — is where programmes go wrong.
Over the past decade, cardiometabolic drug development has undergone a transformation that rivals anything seen in the previous three combined. The rise of GLP-1 receptor agonists didn't just produce effective therapies — it forced a fundamental rethink of what we're studying, how we measure success, and what regulators, payers, and patients actually need to see from an early-phase programme.
For sponsors navigating this landscape, the challenge is no longer simply getting a drug into humans. It's generating the right human data, early enough, to make confident development decisions — in a field where the goalposts are visibly moving.
Here's what that means in practice.
For most of its history, obesity research was defined by a narrow question: does this drug reduce body weight? The GLP-1 era has made that question almost redundant. Of course effective obesity drugs reduce body weight. The question sponsors now face is: what else does your drug do, and how do you prove it?
Obesity is a chronic, systemic disease that drives cardiovascular events, fatty liver disease, kidney dysfunction, sleep apnoea, and type 2 diabetes. Therapies that reduce only weight, without meaningfully addressing these downstream consequences, face an increasingly sceptical audience — from regulators asking for cardiovascular outcome data to payers asking why they should fund a drug that looks like everything already on the market.
Trial design has to catch up with this. Endpoints need to go beyond BMI. Fat distribution — specifically ectopic and visceral fat — is a stronger predictor of cardiometabolic risk than body weight, yet most traditional obesity trials don't measure it systematically. Biomarkers of inflammation, adipokine profiles, body composition imaging, and patient-reported outcomes around appetite and quality of life are no longer optional add-ons; they're increasingly expected.
At the same time, placebo-controlled designs are under ethical pressure. When effective therapies exist and their cardioprotective benefits are established, keeping patients on placebo for extended periods is harder to justify — scientifically and ethically. Alternative designs, including active comparator studies and putative placebo approaches using statistical matching to historical data, are becoming the direction of travel.
Diabetes drug development has undergone a similar shift. For decades, HbA1c was the central endpoint. A drug that lowered blood glucose was considered a success. That era is over.
Today, regulators, clinicians, and payers expect new diabetes therapies to demonstrate cardiovascular benefit, renal protection, and broader metabolic improvement. Glucose reduction is now the floor, not the ceiling. Differentiation comes from everything else a molecule can do.
This has raised the stakes for early-phase development significantly. Phase I and II thinking increasingly overlap. Exploratory biomarkers, mechanistic readouts, and metabolic assessments that once belonged exclusively to later stages are now integrated from the outset — not to prove efficacy early, but to demonstrate that the biology is moving in the right direction before committing to large, expensive Phase III programmes.
For smaller biotechs, where much of today's cardiometabolic innovation originates, this shift presents a particular challenge. Strong preclinical data doesn't automatically translate into a well-designed clinical plan. The markers that matter, the patient populations that are appropriate, and the endpoints that will satisfy regulators twelve months later all require early-phase expertise that many emerging development teams don't have in-house.
Two of the most important — and most challenging — areas in cardiometabolic development receive less attention than they deserve in early-phase planning.
MASLD (metabolic dysfunction-associated steatotic liver disease), formerly NAFLD/NASH, sits at the intersection of obesity, diabetes, cardiovascular risk, and systemic inflammation. Its prevalence is extraordinary — yet most patients don't know they have it, and the diagnostic landscape remains fragmented. Non-invasive tools like MRI-PDFF, transient elastography, and clinical risk scores have improved significantly, but regulatory expectations haven't fully caught up: biopsy remains the standard for many confirmatory endpoints, despite its invasiveness and the recruitment barriers it creates.
Diabetic kidney disease presents similarly. Nearly half of all patients with type 2 diabetes develop DKD — the leading cause of kidney failure globally. The therapeutic landscape is improving, with SGLT-2 inhibitors showing renal and cardiovascular benefit beyond glucose control. But early identification and early intervention remain critical, and early-phase studies need to be designed around the full metabolic complexity of this population, not just kidney endpoints in isolation.
Both areas demand more from trial design than traditional frameworks offer — better screening tools, more precise patient stratification, and endpoint strategies that reflect both biological plausibility and regulatory reality.
Running early-phase cardiometabolic studies is not the same as running other Phase I work. These are complex, multi-system diseases with heterogeneous patient populations, ethically sensitive protocols, and endpoint requirements that span clinical pharmacology, laboratory science, imaging, and biomarker strategy simultaneously.
Renal and hepatic impairment studies — an often-overlooked component of cardiometabolic development — are a useful illustration. On paper, they look straightforward: defined patient categories, clear guidelines, predictable PK endpoints. In practice, they're frequently underestimated. Stable moderate hepatic impairment patients are rare in Western Europe. Renal impairment cohorts require access to a full spectrum of CKD stages, dialysis capability, and clinicians who understand impaired-population pharmacokinetics. Sponsors who assume any Phase I unit can run these studies often discover, too late, that specialised infrastructure is the difference between a smooth study and a stalled one.
What early-phase cardiometabolic development actually requires is integration: clinical pharmacology, biomarker science, laboratory analytics, patient access, and regulatory insight working together from the outset — not as separate functions that hand off to each other at predetermined intervals. When those disciplines are aligned from first-in-human through proof of mechanism, development becomes more efficient, more predictable, and more scientifically grounded.
The next generation of cardiometabolic trials will combine scientific rigour with operational precision. Endpoints will be broader, patient stratification will be more sophisticated, and the frameworks for generating decision-ready data early will look meaningfully different from what was considered standard just a few years ago.
Multi-agonist therapies — GLP-1/GIP/glucagon combinations already in development — will require trial designs capable of measuring multiple biological pathways simultaneously. Personalised approaches, stratifying patients by phenotype or predicted drug response, will move from aspiration to standard practice. Laboratories will be strategic partners in endpoint selection, not just sample processors.
For sponsors working in this space, the message is clear: the programmes that will succeed are those that invest in getting the early-phase strategy right — not as a box-ticking exercise before the 'real' work begins, but as the foundation on which every subsequent development decision rests.
The science is advancing rapidly. The question is whether the execution can keep pace.
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Rethinking Early-Phase Cardiometabolic Development — From Endpoints to Execution covers obesity trial redesign, the new reality of diabetes development, MASLD and DKD study challenges, best practices in trial design, and a deep-dive into renal and hepatic impairment studies. Written by Prof. Thomas Forst, CMO at hVIVO, with perspectives from across our cardiometabolic team.