Metabolon reveals a new ally for drug research and development programs: Picking program winners and demonstrating their value
Today’s biopharma companies are faced with extreme competition to secure support from investors, approval from regulators and buy-in from payers. How can a company and its new molecule break through the noise to overcome these challenges? Enter metabolomics, the study of metabolites-- small-molecule end products of the metabolism collectively known as the metabolome. Metabolomics can instantaneously provide a snapshot of the entire physiology of a living being, enabling a deep understanding of health, disease and treatment response, whether influenced by genes, the environment, epigenetics or the microbiome.
Metabolon’s superior methodology and vast metabolite library allow for the capture of a complete story about your molecule at every stage, providing valuable input that builds a robust story about your data to shape a comprehensive Global Value Dossier, or what we call a Program Development Dossier.
The barriers to program success for biopharma, whether success comes in the form of an asset sale or an approved therapy, are immense. The cost of securing approval for a new drug is now estimated at $2.6 billion, which has increased 145 percent over the last 10 years due in large part to an extremely high failure rate. But what is at the heart of the failure rate? When scientists and biopharma leaders reflect on the source of high drug attrition rates, they cite many factors including: failure of preclinical development models to predict treatment efficacy, safety issues or difficulty differentiating between responder and non-responder patients. A commonality to all these issues and their associated risks is that critical pieces of information are lacking or unclear, leading to a foggy decision-making landscape.
How can clarity emerge from the fog?
Are there better ways to clarify decisions along the R&D continuum to increase the probability that a molecule directed against a target will have efficacy in humans without compromising safety? Typically, this information is sought through two extremes:
- Profiling approaches (e.g. RNASeq, proteomics, etc.) which create overwhelming amounts of data.
- Assays that were selected based on the putative mechanism and target biology.
The former is difficult to wade-through to discern meaningful information and the latter relies on picking the right markers in advance, which frequently does not occur. Therefore, data that occupies a middle ground between these extremes is needed – something that is comprehensive, meaningful and readily interpreted. Metabolomics data provides a view of these properties and helps to enrich decision making from discovery through the clinic. Hence, small and large biopharmaceutical companies are constantly on the look-out for approaches that deliver this type of data.
Biopharma companies are routinely bombarded by technologies that promise “the next great thing” that will “revolutionize drug discovery.” Clearly some of these can help incrementally, some will have little utility and some will provide true promise. The question is, how can you discern the best options for your program? One rubric for this is to reflect on what we described above, selecting the method that will deliver clarity through the fog – data that is comprehensive, meaningful and readily interpreted, and data that dynamically assesses a living system and links it to physiological changes induced by disease and drug response. These qualities describe metabolomics data.
Metabolomics provides comprehensive and meaningful insight into each stage of the drug development process, allowing drug developers to attain signals for both safety and efficacy (as well as their associated biomarkers). This capability informs decision-making across the drug development continuum. Importantly, successes driven by these insights accumulate along the way and across programs, suggesting strong potential for metabolomics to aid in reducing drug attrition. In isolated programs, these insights help build confidence, discharge risk and illuminate the value of the program. Regardless to the challenge at hand for biopharma, the Program Development Dossier approach presents the missing link to deliver winning drug programs.
Metabolomic insights empower effective decision-making
Metabolomics enriches R&D decision-making because of the fundamental properties of what it surveys – the metabolome – all the small biochemicals (metabolites) that circulate in the body or in a cell. Metabolomics is particularly important in creating clarity for drug research and development because nearly all the influences that effect physiological processes (disease, target biology, off target activity) affect the metabolome [Image 1]. Hence, measuring with metabolomics provides a consensus report for molecule action in the context of the model being used. Finally, because the metabolome and metabolic pathways are so extensively mapped, this consensus report is readily interpretable.
Of course, the fundamental strengths of metabolomics are not new. What is new is that many biopharmaceutical companies have embraced the broadening view that metabolomics is a first-line tool for drug development. This video features leaders sharing their experience with metabolomics and Metabolon.
Enter the Program Development Dossier
Staples of drug research and development are to gain clarity on the effects of the target-molecule combination and obtain biomarkers that can accompany the program into clinical development. The importance of these insights and biomarkers is escalated when pursuing novel molecules and targets or entering a highly competitive space. As described above, metabolomics provides a powerful synergy to the standard data for gaining these important staples.
As companies build their Program Development Dossier – a comprehensive data package that includes detailed scientific insight into the molecule’s mechanism of action (MoA) and relevant clinical biomarkers – layering in informative data and biomarkers from metabolomics will help to build the most robust story to secure funding and move one step closer to approval. Ideally, studies begin in efficacy models, continue through preclinical development, and continue into first in human studies. In this way, the most translatable markers and understanding of the target/molecule combination will occur [Image 2].
Dossier data revealed through Metabolon’s proprietary untargeted metabolomics solution provides the framework to make a stronger, more confident and more valuable case for a molecule in a shorter timeframe and can travel through the drug development process. This dossier is equipped with translatable biomarkers, clarity on how the molecule/target combination is unique. With this type of Program Development Dossier, both large and small biopharma can have access to credible, highly relevant data that clearly demonstrates the potential value of their development program. In addition, this data can help organizations build an infrastructure in the form of translatable biomarkers that can be leveraged for future programs.
Some common questions that are addressed in a Program Development Dossier fueled by metabolomics are:
- Which model is most translatable/relevant?
- Is there a clear pharmacodynamic (PD) and efficacy signal from my animal model?
- Do I have blood biomarkers for monitoring PD and efficacy, including in non-rodent models?
- Will the biomarkers translate to humans?
- Are there any obvious liabilities with the molecule?
- Do I have the data to support a clear, compelling MoA that translates from animal models to humans?
- Is the molecule likely to achieve commercial success based on the competitor landscape?
- Do the biomarkers have potential for selecting sub-groups for trials or identifying responders?
- What is the clearest path for the next development milestone?
Insights from the dossier
Project teams are increasingly using metabolomics to enrich their drug research and development programs to solidify stakeholder support. Importantly, this use is agnostic to the target class (e.g. GPCR, enzyme, nuclear receptor) as it is recognized that nearly all areas of target biology on route to efficacy will impact metabolic pathways. Below are several abstractions from various organizations’ metabolomics-driven Program Development Dossier initiatives. [Image3].
Case studies of the Program Development Dossier in action
Markers of acute renal toxicity enable screening less toxic chemotypes
While in early development of a molecule directed at a novel target for lowering cholesterol, metabolomics screening revealed markers associated with acute renal failure in mice. Conventional markers did not clearly signify the issue or explain it. The metabolomic biomarkers provided confidence that the effects were clearly off-target and these markers were used to screen other chemotypes to show that the toxicity was isolated to a particular chemotype. This insight provided a potential way forward for the program. This example highlights the peril of relying solely on established markers as they were ineffective in reflecting and explaining the toxicity. In contrast, metabolomic fingerprinting provided clarity and a way forward [REF 2 and 3].
Simple blood biomarkers for assessing response add to the development toolbox in NASH
Endpoints for nonalcoholic steatohepatitis (NASH) trials have many disadvantages including reliability. Simple blood biomarkers are highly desired. The need is amplified since there are so many novel targets in the NASH pipeline - quickly knowing if the program is heading in the right direction (i.e. hitting the target, signs of efficacy) is critical. Leveraging metabolomics, investigators at Gilead bolstered the confidence that they were on the right track in their successful phase II trial of GS-0976 by discovering several metabolite markers of efficacy. These biomarkers can accompany future development for reading out the pharmacodynamic activity or response of GS-0976 [Ref 4 and 5].
Biomarkers of acute inflammatory organ condition in early phase clinical trial delineated by metabolomics
Using metabolomics in clinical development can be beneficial to subtype individuals who respond but also may indicate who will experience adverse events. Metabolomics data showed a clear association with subjects that exhibited severe abdominal pain and inflammation of a specific organ. Over a dozen metabolite markers from two different classes – one related to the primary organ dysfunction and the rest to the activity associated with the inflammation clearly distinguished the group experiencing the adverse event. These metabolites can be used to monitor subjects in subsequent studies for early signs of the adverse event.
One route to finding molecules with novel MoAs is through phenotypic screening. One sponsor had discovered a potent angiogenesis inhibitor with similar potency to an approved drug. Despite it successfully moving through development, the MoA was unknown and Pharmacodynamic biomarkers were lacking. Metabolomics showed that the underlying MoA was clearly distinct from the approved drug and unique to any angiogenesis inhibitor described on the market. This provided a powerful leg-up in distinguishing their molecule from the competitors and identifying PD biomarkers that could accompany it into development.
Summary of what it can do
These examples highlight the importance of adding metabolomics to drug discovery and development programs. The clarifying enrichment and translatable biomarkers provided are clear assets embedded within the Program Development Dossier. The Program Development Dossier is a new companion to ultimately help pick the winners, determine how best to advance them and to demonstrate the value of the program. To learn more about how this approach can help your program read our whitepaper or or contact us today to get started.
 DiMasi, Joseph A., et al. “Innovation in the pharmaceutical industry: New estimates of R&D costs.” Journal of Health Economics Volume 47, (2016): 20-33. https://www.sciencedirect.com/science/article/abs/pii/S0167629616000291?via%3Dihub
 Zgoda-Pols, Joanna R., et al. "Metabolomics analysis reveals elevation of 3-indoxyl sulfate in plasma and brain during chemically-induced acute kidney injury in mice: investigation of nicotinic acid receptor agonists." Toxicology and applied pharmacology 255.1 (2011): 48-56.
 Wang, Ganfeng, and Walter A. Korfmacher. "Development of a biomarker assay for 3‐indoxyl sulfate in mouse plasma and brain by liquid chromatography/tandem mass spectrometry." Rapid Communications in Mass Spectrometry: An International Journal Devoted to the Rapid Dissemination of Up‐to‐the‐Minute Research in Mass Spectrometry 23.13 (2009): 2061-2069.
 Loomba, Rohit, et al. “GS-0976 reduces hepatic steatosis and fibrosis markers in patients with nonalcoholic fatty liver disease.” Gastroenterology 155.5 (2018): 1463-1473.
 Charlton, Michael, et al. " Serum Acylcarnitines Are Biomarkers of Magnetic Resonance Imaging‒Proton Density Fat Fraction Response in NASH Patients Treated With the ACC Inhibitor Firsocostat (GS-0976)." Presented at EASL: The International Liver Congress™ 2019, April 10–14, 2019, Vienna, Austria