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SERES THERAPEUTICS, INC. filed this Form 10-K on 03/06/2019
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A placebo-controlled, randomized, blinded clinical study published in Gastroenterology in 2015 showed that repetitive FMT delivered via enema weekly for 6 weeks induced clinical remissions in 24% of patients with active UC compared to 5% receiving placebo (Moayyedi et al., Gastroenterology, 2015).   This study utilized endoscopy, a direct visualization of the colon, before and after treatment to assess the efficacy of FMT, thus demonstrating the role of the microbiome in treating active UC. A subsequent randomized, placebo controlled, blinded study of FMT delivered via enema 5 days per week for 8 weeks demonstrated similar clinical remission rates: 27% receiving FMT and 8% receiving placebo (Paramsothy et al., Lancet, 2017). Most recently, a study of FMT delivered by a colonoscopy followed by 2 enemas to UC patients resulted in similar outcomes:  32% receiving donor-FMT and 9% receiving autologous control (Costello et al, JAMA, 2019). We announced top-line clinical data from our Phase 1b clinical trial for SER-287 in October 2017.  In this trial, patients with mild-to-moderate UC, receiving a vancomycin pre-treatment followed by a daily oral dose of SER-287 for 8 weeks achieved a 40% rate of clinical remission compared to no clinical remission for treatment with placebo. This analysis followed the intent-to-treat, or ITT, “worst case” analysis used for drug registration studies in which missing data is counted as failure.


Data from cancer patients undergoing allo-HSCT show the influence of the microbiome on patient survival. An observational study of allo-HSCT patients following allo-HSCT demonstrated that 3-year survival in patients with a low diversity microbiome was 36% whereas survival in patients with a medium to high diversity microbiome was ≥60%. Excess mortality in the low diversity subset was driven by deaths due to infection and GvHD, not the underlying cancer itself (Taur et al, Blood, 2014).  A follow up from the same researchers looked at allo-HSCT patients receiving transplants who are at highest risk of GvHD and showed a greater than 5-fold increase in mortality was correlated with microbiome composition. (Jenq et al., Biol of Blood and Marrow Transplant, 2015).  


Two studies in mouse cancer models, both published in Science in 2015, demonstrated that the anti-tumor response to immune CPIs could be enhanced by altering the microbiome (Velizou et al., Science 2015; Slvan et al., Science 2015). More recently, independent groups from MD Anderson, the Institute Gustave Roussy in Paris, France, and the University of Chicago have published data from human studies showing that cancer patients who successfully respond to immune CPIs tend to have a distinct microbiome from patients who do not respond. Moreover, when human fecal samples from responding and non-responding patients are transferred into mice, these have been shown to exhibit the same response to CPIs in tumor model experiments as their human donors (Golpalakrishnan et al, Science, 2017; Routy et al, Science, 2017; Matson et al, Science, 2018).  Taken together, these results suggest that microbiome therapies might improve the efficacy of CPIs in treating cancer.


There are currently no microbiome therapeutics approved by the FDA. We believe that the ability to develop drugs that are able to modulate the microbiome and return a dysbiotic microbiome to its healthy state presents a significant opportunity to improve human health.

Our Microbiome Therapeutics Platform

We have developed the leading microbiome therapeutics platform, which we believe enables us to significantly reduce the time typically required to advance therapeutics to the clinic, and ultimately, to the market.  We use reverse translation, the practice of driving discovery based on human data sets to improve the translatability of a preclinical program.  Specifically, we start with data sets from both healthy subjects and patients to delineate at high-resolution the composition of the microbiome and physiological state of subjects and identify specific signatures in the microbiome that associate with disease or the onset of disease; these in-human insights are leveraged in preclinical drug design and development.

Our discovery process begins with human data derived from clinical trials and cohort studies, which we use as a basis for designing our Ecobiotic microbiome therapeutic candidates. We compare healthy, normal colonic microbiomes to those in an unhealthy dysbiotic or disease state, revealing the ecological and functional differences between various states of disease and during the transition from health to disease or vice versa. We then develop our Ecobiotic microbiome therapeutic candidates to target these differences. Our clinical data from the SER-109, SER-262 and SER-287 programs, and microbiome data generated with external collaborators, serve to instruct us on how the introduction of certain keystone microbes have the potential to restructure a dysbiotic colonic microbiome and shift it to a non-disease state.

We have developed a proprietary suite of bioinformatics and computational tools, which facilitate our insights into the human microbiome.  Using whole metagenomic shotgun sequencing, and our proprietary, curated, reference database of novel bacterial genomes, our algorithms enable us to track changes in the microbiome at the level of bacterial species and individual strains.  We have also developed tools integrating gene profiling and metabolomics data (the small molecules made by the microbiome) with genomic data (the collection of bacteria defined by sequencing) to understand the functions related groups of organisms contribute to the state of disease or health.  Further, we have established de novo analytics for pharmacokinetic and pharmacodynamic assessments of microbiome therapeutics.


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