Obesity Treatment Development: Challenges and Future Focus
Biopharmaceutical drug development is challenging, but incorporating AI and simulation models can support progress.
Biopharmaceuticals are a fascinating class of therapeutics that leverage our own cells, proteins, and genes to treat disease. Today, metabolic and weight-loss drugs—including GLP-1s—sit front and center in the biopharmaceutical space, driven by a growing obesity and metabolic disease burden and subsequent demand.
Although often celebrated as “miracle drugs” for the significant weight loss and improved glucose control they facilitate, GLP-1s are not a magic bullet. These therapies are costly, can cause uncomfortable side effects, and have high levels of discontinuation.
As a result, researchers are working toward the next generation of metabolic and weight-loss drugs, aiming to preserve existing benefits while minimizing the current limitations. Approaches range from single appetite-suppressant drugs to treatments targeting multiple hormones, as well as experimental monoclonal antibodies designed to prevent muscle tissue breakdown during weight loss.
While these therapies dominate the headlines, it is important to recognize the decades of work that went into their development. Regardless of modality or indication, successful biopharmaceutical drug development is no easy feat.
As Senior Scientist at Superluminal Medicines, Dr. Alix Rouault is well-positioned to share insights in this area, particularly as the company works to bring G protein-coupled receptor (GPCR)-targeted biased ligand approaches for obesity into clinical trials. Technology Networks spoke with Rouault ahead of his session on biopharmaceutical drug discovery at this year’s American Society for Pharmacology and Experimental Therapeutics conference to explore development challenges, the obesity drug landscape, and the importance of incorporating AI and simulation models into pipelines.
What are the biggest challenges in translating preclinical findings into first-in-human trials during biopharmaceutical drug development?
Alix Rouault, PhD (AR):
Early discovery remains challenging across all sectors, and developing species-agnostic medicine is particularly difficult due to several key factors. From a biological perspective, success depends heavily on the specific target and its species homology. At Superluminal Medicine, we focus on complex GPCR targets. While we design and test small molecules in vitro against the human versions of a target, these immortalized cell lines often deviate from healthy cells.
Furthermore, much remains unknown about GPCRs. For instance, in our melanocortin program, the melanocortin-4 (MC4R) receptor can function independently but is regulated by MRAP2 and other accessory proteins, adding layers of signaling complexity. Consequently, we can only approximate the effects of new treatments at this stage.
Melanocortin program
The melanocortin program is an obesity drug-development effort focused on targeting the MC4R receptor due to its role in energy homeostasis, food intake, and appetite regulation. MC4R variants are the most common genetic contributors to obesity in the general population and are also observed in rare genetic conditions that cause obesity; a hallmark of MC4R dysfunction is constant hunger. Superluminal medicine’s drug candidate uses a biased ligand approach, meaning that only a select subset of signaling pathways is activated.
Advancing lead candidates with acceptable pharmacology to in vivo testing helps us understand phenotypic effects, but species differences continue to complicate the data. Sequence and distribution differences between lower and higher mammals, along with variations in the proteome of target-expressing cells, mean that animal results only indicate potential human response. This means that a candidate might be halted due to a significant cardiovascular response in a test species that would be absent in humans and vice versa.
Although this process is costly and time-consuming, the resulting science is truly fascinating.
IH:
Reflecting on these challenges, what experimental findings have supported the progression of Superluminal’s melanocortin program toward clinical trials?
AR:
The melanocortin system is complex, and setmelanotide is currently the only treatment targeting MC4R for rare genetic and acquired forms of obesity. While MC4R-expressing neurons in the hypothalamic paraventricular nucleus trigger potent hunger suppression when activated, unrefined agonists can affect other receptors like MC1R, which regulates skin pigmentation. Due to setmelanotide’s poor selectivity profile, patients frequently experience skin darkening, which is accentuated around the injection site.
Setmelanotide
Setmelanotide is used to treat obesity caused by rare genetic disorders. Indications for use include acquired hypothalamic obesity, Bardet-Biedl syndrome, and genetic obesity linked to deficiencies in specific genes controlling appetite: POMC, PCSK1, and LEPR.
However, our team has successfully designed a small molecule with high selectivity for relevant MC4R signaling pathways, representing a significant milestone in small molecule development.
Furthermore, we have addressed the cardiovascular risks associated with specific MC4R signaling pathways in melanocortin treatments. Our team has developed small molecules with remarkable biased signaling profiles to avoid the pathways that have been associated with cardiovascular complications.
Cardiovascular complications associated with MC4R agonists
Research has shown that MC4R activation can increase sympathetic nerve activity, leading to higher heart rates and blood pressure, raising cardiovascular safety concerns. However, other studies have demonstrated that chronic MC4R agonist treatment not only causes weight loss but also improves various metabolic markers, which could be beneficial for cardiovascular health. Ultimately, pathway selectivity and subsequent effects vary, but newer compounds are developed with this in mind.
The combination of superior selectivity and biased signaling, among other parameters, has led to our decision to move these candidates into the clinic.
IH:
With GLP-1 therapies currently dominating the obesity drug market, how do you see GPCR-targeted approaches complementing or differentiating from them?
AR:
Incretin agonists currently dominate the market for pharmacological treatments used for general weight loss. While these are groundbreaking medicines, there are remaining unmet needs. For example, many patients cannot tolerate these medicines due to gastrointestinal side effects. In addition, there are a number of patients who do not respond or who do not reach their weight loss goals with currently available therapies.
Increasing the number of available pharmacological options is essential to help patients find the treatment that works best for them. Given our biological differences, a treatment that is effective for one individual may not be suitable for another. Ultimately, increasing these options will help alleviate obesity-related conditions and improve patients’ quality of life.
IH:
How is Superluminal’s AI-enabled discovery platform helping to identify and prioritize viable drug candidates, including the lead MC4R candidate?
AR:
We utilize AI throughout the drug discovery process to accelerate our efforts and augment what can be accomplished by our lean team of scientists. As an example, we use machine learning-based virtual screening to scan billions of molecules from chemical libraries to predict which compounds will dock to a target of interest.
Furthermore, we developed machine learning models trained on public and proprietary data, that we can use to predict molecules with adverse ADME-tox parameters, allowing us to filter them out of our testing. We even use AI-based image acquisition to increase the throughput and accuracy of our cryo-electron microscopy capabilities, allowing us to cost-effectively capture high-resolution pictures of our chemical candidates interacting with the target.
IH:
How do you think the biopharmaceutical industry will change over the next 5–10 years, and what capabilities will be most critical to remain competitive?
AR:
With the increased understanding of protein structure and dynamics, simulations are becoming increasingly valuable in the drug discovery workflow.
I strongly advise anyone interested in the field to understand the capabilities and power of simulation.
If the progress of in silico tools is not slowed by the current geopolitical situation, virtual screening will eventually become the standard, rather than library testing. However, we are still miles away from relying solely on simulation output; physical testing will remain a non-negotiable step in drug discovery.
Biologists should seek to develop as broad an assay catalog as possible and update it frequently. Determining the accuracy of a simulation with the best available assay is what matters most to ensure quick feedback for model refinement.
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