Do we fully understand what drives a disease or what a drug does in a patient?
When Samantha & Jon opened with “Most drug development is still risky (3% probability of success) and costly” my learning hat was on :) Founders educating investors straight to the point with no small talk, is what I look forward to. Hearing their personal story, Co-Founder and CEO Jon Hu, formerly a consultant at Bain & Co. and Investor at Guild Capital, is a Harvard MBA and Northwestern University-trained biomedical engineer and economics major where he first met Co-Founder and CSO Samantha Dale Strasser, PhD, a former Churchill Scholar at the University of Cambridge and NSF Graduate Research Fellowship-backed PhD in Electrical Engineering and Computer Science at MIT in the Lauffenburger Lab. Samantha’s graduate work built upon the body of research that underlies Pepper Bio’s platform, “The world's first transomics drug discovery and development startup”
Pepper Bio is a drug discovery and biology platform that uses transomics to give researchers access to the most comprehensive understanding of any disease. In addition to genomics (DNA), transcriptomics (RNA), and proteomics (proteins), Pepper Bio’s transomics includes a new, and the most functional omics layer, phosphoproteomics — the analysis of protein phosphorylation. The key to Pepper Bio’s platform is the phosphoproteomic data, which other drug discovery companies have been largely unable to leverage. Phosphoproteomics is a type of proteomics that characterizes proteins with the reversible post-translational modification of phosphorylation, which has a vital role in cellular processes such as cell cycle regulation, signal transduction, and protein targeting. It provides insights that other omics miss since change in phosphorylation status almost always reflects a change in protein activity, which indicates what proteins might be potential drug targets. The current challenges we see in the industry are:
1. Lack of understanding biological activity
a. Many factors influence health and disease. Historically, researchers looked at the presence of a particular molecule to gain insights on what could potentially happen in the body by understanding how much of a particular molecule or molecules are present in a cell, but the important part is knowing what that molecule is actually doing. The presence of a molecule alone may or may not be indicative of disease because a molecule can do many different things or nothing at all. Just knowing the amount of those molecules does not give you information on their activity.
2. Looking in the wrong places
a. Currently, drug developers will pre-select a few narrow regions of biology to probe into by looking at what’s been done before. If the historical knowledge didn’t capture all the relevant receptor/protein locations, then the developers will miss looking into those locations. In many instances, the places they didn’t look at causes the drug to be ineffective or too toxic and drugs will often fail as a result.
3. Correlation is not causation
a. Due to the sheer number of variables when looking at omic data, researchers will inevitably end up identifying many statistically significant results just by chance alone. There are too many results for researchers to follow-up on. Furthermore, even if they could follow-up on all of them, they wouldn’t want to because it’ll take too long and be too expensive.
This is where the guessing games begin, drug developers make many assumptions and guesses when designing a drug in its path towards approval. Unfortunately, many of these assumptions and guesses are wrong, which leads to the eventual failure of the program. In recent decades, the use of multi-omics data (genomic, transcriptomic, metabolomic, etc) has resulted in high-throughput screening that, by allowing quantitative measurements of many targets, has exponentially increased the volume of scientific data available. However, human diseases are complex and involve many interrelated pathways, which can lead to the identification of different molecular targets. As a result, multi-omic data has been a key tool employed in driving drug discoveries in recent years due to its ability to uncover optimal drug targets. Data is initially collected from patients and integrated to create their molecular profiles, which are then matched to previously defined disease profiles that can guide the selection of treatment. This is achieved either through a match to known biomarkers, omics signatures or network/pathway signatures. The appropriate molecule is then developed based on this match to improve the chance of successful treatment and reduce the probability of side effects in a certain population - given the $200B+ in annual cancer treatments, there is more than enough TAM in each patient population to create a blockbuster drug. However, proteins are the major effectors of cell functions through changes in their posttranslational modifications (PTMs) and abundance, reflected also on changes in their interactome with effects on cell phenotypes. Accordingly, several important aspects of the drug discovery process, including target identification, mechanism of action determination and biomarker identification as well as drug repositioning, require complete understanding of the effects of drugs on protein phosphorylation in relevant biological systems. Therefore, it is critical to also consider proteomics and phosphoproteomics along with other omics data to understand disease development and subtypes, as they can better capture the functional state and dynamic properties of a cell in a systematic way, to identify the precise underlying molecular mechanism and discover personalized biomarkers, signatures, and treatments.
Pepper Bio’s WOW factor, the startup is already able to develop precision therapeutics for nearly any disease. This helps them to strategically focus on high prevalence indications with a high disease burden. Initially, the startup is building a portfolio of oncologic assets, eventually they will move into neurodegenerative disorders, inflammatory disorders and then metabolic and other disease categories thereafter. Its important to emphasize they’re the world’s first transomics drug discovery startup that includes genomics, transcriptomics, proteomics, and phosphoproteomics all in one precision medicine development and discovery platform. They not only identify the targets from the beginning of the clinical trial, but also stay with partners throughout the entire process — from lead prioritization to patient selection, and finding the right drug combinations, to indication expansion. Pepper Bio is the only purpose-built drug discovery platform capable of using transomics to capture data from the entire biological spectrum to specifically answer drug development’s biggest questions. The Pepper Bio dictionary of novel technologies might just decipher the mystery of phosphoproteomic data.
Keeping our confidential deal memo private, most importantly Pepper Bio is currently hiring so look them up. There are risks here like Phosphoproteomics is a relatively new and highly complex data type and the startup continues to adopt new data, which the startup will need to successfully integrate, including future omic layers, they’re still early in their commercial & regulatory journey, and both Proteomics & Phosphoproteomics need more research in biology.
We’re super excited for this opportunity to join them on this drug discovery journey, and add value as a Board Observer using our improved Longevity metrics.
