VDP-116 [Funding] Mansarover: discovery platform for bifunctional compounds targeting FGF21+TGFß

One-liner: Funding proposal: this group is pioneering a computational strategy to craft safe, novel compounds targeting both FGF21 and TGFß pathways, promising enhanced longevity results and a strategic edge in the longevity research landscape.

Longevity Dealflow WG team

Scientific evaluation: [To be completed after Senior Review - Phase 2]

Business evaluation: [To be completed after Review - Phase 2]

Shepherd: Eleanor Davies

Other squad members: Paolo Binetti; Michele Gallia

Project PI: Co-PI Ram Samudrala, Brennan Overhoff

Simple Summary

This group will deploy a novel computational drug design approach to develop small molecule therapies to promote longevity through complementary metabolic and reprogramming mechanisms, i.e. FGF21 and TGFß pathways respectively. The platform1 accounts for all protein interactions simultaneously, allowing new compounds to target several pathways while avoiding off-target interactions, thereby promoting safety and systemic deliverability, to improve hit rate and efficacy in preclinical models of aging. FGF21 and TGFß pathways have been explored by various groups for promoting longevity and rejuvenation with compelling results in mouse lifespan studies and/or cell models; by targeting both simultaneously with novel compounds, we not only expect better preclinical outcomes via holistic action but also differentiated drug IP which will benefit the competitive ecosystem in the years to come.

Problem

The biological complexity of aging demands interventions that account for this complexity in a tailored manner, i.e. one which cannot be attained through existing drugs and purchasable compounds, so the successful deployment of this platform would represent a critical shift away from single-target and omics-guided screening to robust multi-target and omics-guided design in longevity biotech and pharma. Companies like Bioage and Fauna Bio have shown omics-guided approaches are promising in longevity for screening small molecule libraries, so the tailored omics-guided design implemented in this platform will improve efficacy and hit rate for computationally generated compounds through the exploration of novel chemical space. While some platforms exist for novel small molecule design, these have only been developed and benchmarked for individual target efficacy as opposed to the selective multi-targeting efficacy and off-target mitigation that we have achieved and shown via proteomic modeling.

Opportunity

Transgenic overexpression of FGF21, the “starvation hormone,” increases median lifespan in mice by 30-40%2, notably higher than any small molecule intervention tested by the NIA Interventions Testing Program3 (max. ~20% increase). TGFß signaling has been shown to be highly upregulated during the aging4 and senescence process and plays critical roles in several aging mechanisms with potential anti-aging applications for inhibitory ligands and related gene therapies. Nonetheless, compared to gene therapies, small molecules are significantly more effective as viable therapeutics that can be easily and systemically delivered throughout the body with the potential to safely exert multi-target effects. Internal proteomics analysis showed that top longevity-promoting small molecules bind to several disparate aging-related mechanisms for maximal efficacy. Thus, designing bifunctional compounds to induce FGF21 and inhibit TGFß, which have each been shown to disparately play a role in aging/regeneration, is a highly promising goal for novel multi-target/proteomic drug design approaches which is yet to be achieved by other discovery engines. One potential application for these bifunctional compounds is the treatment of progeria, which is classified as an orphan disease. Being an orphan disease offers a route to accelareted FDA approval for molecules that target its treatment

Solution

Platform

The execution of this proposal would represent a novel and innovative application of this team’s drug design platform, previously funded to develop novel therapies for pain and addiction management (ASPIRE award5, funded NIH STTR6) in addition to non-small cell lung cancer treatment (Buffalo Innovation Accelerator7), to longevity for which its multi-targeting/proteomic approach would be highly useful for generating a number therapies in the years to come.

This platform uses two deep learning architectures, namely a conditional variational autoencoder (CVAE) and conditional graph generative model (CGGM), to condition the generation of new compounds on desirable interaction strengths for ~15,000 proteins simultaneously as benchmarked1 by proteomic molecular docking studies and, recently, ongoing platform proof-of-concept wet-lab validations of synthetic compounds designed to combat non-small cell lung cancer (5/14 designs with preliminary efficacy in tumor suppression models - ~36% in silico hit rate). The design paradigm exists within a broad set of computational tools developed for proteomics-driven drug discovery, used to select top machine-learning designed compounds, collectively referred to as CANDO8, which was initially funded by the NIH Director’s Pioneer Award and multiple NIH NCATS ASPIRE awards. These include tools for predicting drug behavior with respect to efficacy across the proteome/transcriptome, ADME/toxicity, blood-brain-barrier (BBB) permeability, chemical novelty, drug-likeness, and synthetic accessibility. Over numerous validation studies across dozens of indications, CANDO has a ~30% hit rate from in silico predictions to clinic. Recently developed small molecule design protocols allow this team to successfully generate compounds that target multiple proteins and complicated pathways implicated in aging/rejuvenation selectively by deliberately avoiding harmful off-target interactions. This is accomplished through the exploration of novel chemical space and backbones which is uniquely facilitated through omics-scale deep-learning guided design, in contrast to pure screening-based methods which rely on existing compound libraries.

Pilot program (MVR001): Extending Reversine work to new MoA’s, motivated by proteomics

The initial target use of the platform will be to discover Reversine behavioral analogs with an improved efficacy and safety profile, i.e. a novel compound (MVR001) with increased targeting of the FGF21 and TGFß pathways. To accomplish this, Reversine along with behavioral analogs of Reversine will be designed to serve as gold standards/positive controls in critical senescence experiments followed by the design and testing of compounds optimized for desirable FGF21/TGFß activity and safety (MVR001). A recent study9 by a collaborator of this team demonstrated the utility of Reversine, a small molecule reprogramming factor replacement, for reversing several hallmarks of cellular senescence while protecting against DNA damage. A related study10 demonstrated a similar experimental protocol for demonstrating the senescence-reversing effects of Nanog induction with no signs of tumorigenesis. This group will utilize vetted assays and their drug design method to radically improve Reversine and formerly identified compounds known to promote longevity/related phenotypes by modifying their interactions to optimize for TGFß inhibition and FGF21 induction. Proteomics analysis performed internally by this team, in collaboration with HMS, and by other groups11 for approved drugs, reprogramming compounds, and top aging interventions showed that efficacy is often achieved through binding to several disparate mechanisms. Preliminary work has already identified TGFß/FGF21-regulatory and ADME-T -related targets to guide small molecule design with hundreds of promising novel candidates.

Workaround pitfalls

a. Achieving selective multitargeting: both design architectures use full proteome interaction targets that encode the desired binding of designed compounds for all (~22K) proteins. Typically we use the modeled interactions of an existing compound as a way to fill these interactions in as a first approximation of the compound behavior we want to sample around. We then employ various proteomics and network analyses along with literature-identified targets to increase/decrease binding to specific proteins related to efficacy in the indication of choice—in this instance, we intend to inhibit the TGFß pathway via direct binding and induce FGF21 through binding to repressive upstream proteins. Once a set of important proteins is identified, design is technically accomplished by modifying the appropriate binding scores in the objective interaction signature and letting the trained models convert this to compounds that will have the desired binding levels across the proteome. Through consensus proteomics approaches using the universe of approved drugs along with databases of proteins with documented implications in ADME/toxicity, we can similarly modify the objective interaction signature to account for off-target interactions. We ensure this behavior is actually preserved in the compounds we design by then modeling their interactions across the proteome and checking how similar these are to the objective interaction signature—by all accounts of benchmarking the design methods for redesigning existing drugs, i.e. creating structurally novel behavioral analogs, we see that our compounds exhibit the holistic and granular disease-implicated interactions we designed them to have.

b. Misregulating TGFß/tumorigenesis: A number of safety measures will be put in place during the design process to avoid potential adverse TGFß regulation and/or cancer. First, we are replicating the interactions of Reversine in initial programs, which when discovered as an aging/senescence intervention by our collaborator, Stelios Andreadis, had no signs of tumorigenic properties (Reversine has also found use in other literature as an anti-cancer/tumor compound). With respect to optimizing Reversine for TGFß signaling specifically, we can take additional measures to tweak the objective interaction signature to inhibit and/or avoid interaction with downstream oncogenic proteins drawn from literature/databases.

Experimental plan

Stage 1: IP generation - In vitro screening - TGFß/FGF21 targeting:

  • 16-20 novel longevity-promoting compounds targeting disparate aging mechanisms, i.e. TGFß and FGF21, will be synthesized and tested in senescence reporter assays, as detailed by their collaborator, here12, or a similarly equipped CRO13, depending on the timeline to funding. Specifically, the following markers will be used to indicate senescence: p16 activity, SA-ß-gal, γH2AX, and SASP. With additional investor support, this team will further develop any ≤5µM inhibitors of cellular senescence discovered in Stage 1 or 2 in additional disease models and ADME/toxicology studies.

Stage 2: IP validation - In vivo validation:

  • This team is currently planning to raise angel/VC/partnership funding to support additional synthesis, in vitro validation, in vivo mouse lifespan and model progeria studies with the support of the Harvard Innovation Labs and UB startup ecosystem and with the goal of obtaining adaptive composition of matter IP that can be used to treat progeria or aging. While the proposed budget does not cover this work, this section is included to indicate the team’s strategy following in vitro validations for posterity.

Senescence studies were selected as an intuitive initial phenotypic screen for novel compounds designed for longevity in this proposal (as well as being the means through which Reversine was initially identified by collaborator, Stelios Andreadis—keeping consistent with this). A number of readouts were selected that are considered gold-standard in the literature (p16 activity, SA-ß-gal, SASP) and provide additional information regarding the safety/relevance to aging hallmarks of delaying/reversing senescence, e.g. γH2AX for measuring DNA damage. Moreover, Dr. Andreadis, to who this team will subcontract experimental work, has expertise running these assays and already developed dynamic reporters for senescence. A detailed technical approach/justification of senescence experiments can be found here. Using this initial phenotypic screen to hone in on potential hits prior to focusing on proof of mechanism will be more efficient and align better with this team’s holistic/proteomic approach to drug discovery.

Plan and IP Roadmap

Months

As progeria is an orphan disease, closely related to aging phenotypes and the mechanisms and assays detailed here, seeking accelerated approval for this indication will offer an immediate path to commercialization to provide additional capital while aging studies are conducted in mice and humans. Mansarover will follow the example set by Eiger Pharmaceuticals for seeking accelerated approval for Lonafarnib. I.e., we expect to obtain orphan status for compounds with efficacy in progeria models and will subsequently seek additional Priority, Breakthrough, and Rare Pediatric Disease designations by leveraging advantages we discover and intended broad anti-aging effects. Mansarover will seek simultaneous IND filing for these compounds in the context of the aging indication which will inherently require longer clinical studies. The purpose of designing compounds for progeria and longevity outcomes and the subsequent parallel approval pipeline is to reach the market sooner than other drugs only undergoing clinical aging studies to generate additional capital for ongoing studies, future programs, and early-investor incentives.

This team has already formed Mansarover, the company that will license platform technology and subcontract initial experiments (budgeted for in the proposal) from the University at Buffalo. Chemical IP will be held by Mansarover as trade secrets during preclinical studies and protected under NDA/confidentiality agreements while working with external CROs (and UB). Following the identification of some set of clinical candidates we will seek IND filing and follow industry standards for subsequent CoM patent protection.

Mansarover’s goals and methods align with several big players in the field now—most significantly, Ichor Life Sciences and Rejuvenate Bio. Ichor Life Sciences has invested in a number of anti-senescence programs and as of writing this, Mansarover is engaged in talks with Ichor officers with a formal pitch planned for early September 2023 which will increase the scale and scope of the studies proposed here. Ichor has thus far informed experiment design and will provide additional expertise if an investment is established. Moreover, Rejuvenate Bio is currently exploring gene therapies for FGF21/TGFß targeting in a similar fashion to the objectives proposed here. However, Mansarover is pursuing this in the context of small molecules which are generally easier to optimize deliverability/bioavailability for but have historically been difficult to design in a multitargeting context (which the platform solves for). Following initial phenotypic screens (senescence studies), and ADME/toxicology panels Mansarover will likely seek partners/perform additional fundraising for in vivo and clinical studies for which Rejuvenate Bio could be of potential support given alignment of goals.

Relevance to longevity

The goal of this research is to produce novel compounds that safely reverse aging in human cell models. Depending on the outcome of follow-up work, these leads may yield a drug to promote longevity and/or treat/prevent one or many age-related diseases byhttps targeting disparate mechanisms of aging. In addition to yielding compounds to functionally and safely reverse aging in human cells, this work could demonstrate the viability and necessity of integrating proteomics, transcriptomics, and cheminformatics analyses with sophisticated deep learning methods to successfully promote longevity. That is to say, traditional, single-target approaches to drug discovery and screening are insufficient to therapeutically confront aging.

Team

Ram Samudrala

Dr. Ram Samudrala received his PhD from University of Maryland in Computational Biology before pursuing postdoctoral research at Stanford University in Structural Biology. Dr. Samudrala currently is a Professor and Chief of the Division of Bioinformatics at the University at Buffalo, leading the development of Computational Analysis of Novel Drug Opportunities (CANDO) platform for drug discovery, repurposing, and design. Dr. Samudrala was awarded the NIH Director’s Pioneer award for the development and deployment of this platform in the repurposing context across numerous indications and closely works with a number of experimental labs/groups around the world and at the University at Buffalo, including the Andreadis laboratory which specializes in anti-senescence methods.

Brennan Overhoff

Brennan Overhoff is a cofounder and CEO of Mansarover, a platform drug discovery company for longevity, and a student at Harvard University, studying Developmental and Regenerative Biology. Brennan has conducted research with Dr. Samudrala for a number of years and led the development of deep-learning-guided protocols for novel drug design. Brennan is also a member of the Harvard Innovation Labs for commercialization support and Gladyshev lab at Harvard Medical School where he is extending his work on longevity therapeutic development and target prediction.

Collaborators

Stelios Andreadis

Dr. Stelios Andreadis received his PhD from the University of Michigan in Chemical Engineering followed by postdoctoral studies at Harvard Medical School. Dr. Andreadis currently leads a lab at the University at Buffalo specializing in stem cell bioengineering; vascular, skin and gland tissue engineering and regeneration; molecular design of biomaterials; protein and gene delivery, and lentiviral arrays for high throughout pathway analysis of stem cell differentiation and reprogramming, to name a few. His lab developed and is equipped to run a number of assays and reporters to measure cellular senescence relevant to this proposal for which Dr. Andreadis’ expertise will be utilized.

Zackary Falls

Dr. Zackary Falls received his PhD from the University at Buffalo in Computational Chemistry with a research focus on drug discovery and pharmacoinformatics, i.e. the intersection of structural bioinformatics, chemoinformatics, and clinical informatics.

William Mangione

Dr. William Mangione received his PhD from the University at Buffalo in Biomedical Informatics with a research focus on proteomics-driven drug discovery and integrating this with network and pathway/transcriptomic datasets.

Budget

Stage 1: 12 months

Design synthesis: $50,000

Reagents and supplies: $12,500

Salaries: $12,500

Paid by VitaDAO: $75,000

Overhead (10%): $7,500

Total amount requested: $82,500

References

  1. Overhoff, B., Falls, Z., Mangione, W., & Samudrala, R. (2021). A Deep-Learning Proteomic-Scale Approach for Drug Design. Pharmaceuticals, 14(12), 1277. University at Buffalo, Department of Biomedical Informatics, Jacobs School of Medicine and Biomedical Sciences.Pharmaceuticals | Free Full-Text | A Deep-Learning Proteomic-Scale Approach for Drug Design
  2. Zhang, Y., Xie, Y., Berglund, E. D., Coate, K. C., He, T. T., Katafuchi, T., Xiao, G., Potthoff, M. J., Wei, W., Wan, Y., Yu, R. T., Evans, R. M., Kliewer, S. A., & Mangelsdorf, D. J. (2012). The starvation hormone, fibroblast growth factor-21, extends lifespan in mice. eLife, 1, e00065.
  3. National Institute on Aging. (2023). Supported Interventions - Interventions Testing Program (ITP). U.S. Department of Health & Human Services. https://www.nia.nih.gov/research/dab/interventions-testing-program-itp/supported-interventions
  4. Tominaga, K., & Suzuki, H. I. (2019). TGF-β signaling in cellular senescence and aging-related pathology. International Journal of Molecular Sciences, 20(20), 5002. IJMS | Free Full-Text | TGF-β Signaling in Cellular Senescence and Aging-Related Pathology
  5. National Center for Advancing Translational Sciences (NCATS). (2023). 2020 NCATS ASPIRE Reduction-to-Practice Challenge Winners. https://ncats.nih.gov/aspire/funding/2020ChallengeWinners#c1
  6. National Institutes of Health (NIH). (2023). HEAL Initiative: America’s Startups and Small Businesses Build Technologies to Stop the Opioid Crisis (R41/R42 - Clinical Trial Optional). National Institute on Drug Abuse (NIDA); National Center for Advancing Translational Sciences (NCATS) https://grants.nih.gov/grants/guide/rfa-files/RFA-DA-19-020.html
  7. University at Buffalo (UB). (2023). Buffalo Innovation Accelerator Fund. Innovation Hub. Buffalo Innovation Accelerator Fund - Innovation Hub - University at Buffalo
  8. Mangione, W., Falls, Z., Chopra, G., & Samudrala, R. (2020). cando.py: Open Source Software for Predictive Bioanalytics of Large Scale Drug–Protein–Disease Data. J. Chem. Inf. Model., 60(9), 4131–4136. https://pubs.acs.org/doi/abs/10.1021/acs.jcim.0c00110
  9. Rajabian, N., Choudhury, D., Ikhapoh, I., Saha, S., Kalyankar, A. S., Mehrotra, P., Shahini, A., Breed, K., & Andreadis, S. T. (2023). Reversine ameliorates hallmarks of cellular senescence in human skeletal myoblasts via reactivation of autophagy. Aging Cell.
  10. Mistriotis, P., Bajpai, V. K., Wang, X., Rong, N., Shahini, A., Asmani, M., Liang, M-S., Wang, J., Lei, P., Liu, S., Zhao, R., & Andreadis, S. T. (2017). NANOG Reverses the Myogenic Differentiation Potential of Senescent Stem Cells by Restoring ACTIN Filamentous Organization and SRF-Dependent Gene Expression. Stem Cells, 35(1), 207–221. https://academic.oup.com/stmcls/article/35/1/207/6421117?login=false
  11. Hu, Y., & Bajorath, J. (2013). Compound promiscuity: what can we learn from current data? Drug Discovery Today, 18(13-14), 644-650 https://pubmed.ncbi.nlm.nih.gov/23524195/
  12. Andreadis, S. (n.d.). Discovery and Testing the Anti-Aging effects of compounds. University of Buffalo. Validation.pdf - Google Drive
  13. Ichor. (2021, December 6). Ichor’s New Research Article Published by Major Journal Finds Potential Use for New Reactive Probe in Cellular Senescence. Rejuvenation Research. Retrieved from Ichor's New Research Article Published by Major Journal Finds Potential Use for New Reactive Probe in Cellular Senescence - Ichor Life Sciences
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Awesome proposal @michele.gallia and Co-PIs Ram Samudrala, Brennan Overhoff

The approach you’ve taken to craft compounds targeting both FGF21 and TGFß pathways looks fascinating, and as a member of the VitaDAO community, I have a few questions that I believe could help us all understand the depth and potential of your research.

  1. On the Platform’s Computational Approach and Therapeutic Focus:
  • I’m intrigued by how you’ve employed innovative computational methods, including deep learning architectures like CVAE and CGGM, to target specific pathways. Could you share how this approach ensures selectivity without off-target interactions? What safety measures have been thoughtfully put in place? Furthermore, given the complex role of TGFß, how do you plan to prevent unintended consequences, like those related to cancer?
  1. Concerning Experimental Design, Validation, and Strategic Applications:
  • I’m eager to understand the careful planning that went into the experimental design. How did you define the key metrics for success in preclinical models, and what strategies were employed to harmonize the targeting studies? Also, could you shed light on how you chose the specific animal models for validation? I’m particularly curious about the potential of these compounds for diseases beyond progeria, and how you are leveraging progeria’s unique status in this context.
  1. Regarding IP, Regulatory, Commercialization Pathways, and Integration into the Longevity Research Landscape:
  • I’m sure that many of us would love to know more about the strategic planning behind the project. Could you give us some insight into your approach to intellectual property, international patents, and potential licensing? How are you navigating the complex regulatory landscape, especially concerning accelerated FDA approval? Moreover, how does your research fit into the broader longevity landscape, and what collaborations are you considering to enhance impact?

I recognize that these are extensive questions, and I’m genuinely grateful for any insights you may be willing to share. Your work has the potential to reshape our understanding of longevity, and I’m thrilled to learn more from your unique perspective.

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The slide deck is behind a google sign-in.

It looks like there are no preliminary data for this project. From what I can see, this is 2 projects in one. One focused on mimicking reversine and a second on TGFb/FGF.

I get told by my patent people that if it’s ‘obvious’, I can’t patent it. How would ‘like reversine but a little different’ end up being patentable?

Both projects are extreme risk without the prelim data, plus the reliance on the collaborator to do the assays.

I see the claim that there is a 36% hit rate for the in silico design. In that case, a smaller pilot study with 6 compounds might be a better start to provide proof-of-concept.

I would also prefer to focus on one project at a time. Whichever of stage 1a or stage 1b looks better from an ‘ability to patent it’ if successful side should be chosen.

Proposed assays need to include viability. It’s not clear to me why you’d be using lentivirus for these assays. Are there more preliminary data showing the collaborator’s ability to measure senescence without lentivirus?

These two cuts would provide a first milestone of proof-of-concept, and cost ~$70-$75k, or less if no lentiviruses are needed. If the results are exciting, a new VDP would be easy to pass. It would also give a better idea of the hit rate of the platform for longevity and ability of the collaborator to do the proposed experiments.

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Thank you for your comments!

if you send a request to view the presentation I make sure that it is granted

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Hi Vincent here are the answers from Brennan - let me know if you have any followup questions. Also, Brennan is preparing an updated proposal

  1. On the Platform’s Computational Approach and Therapeutic Focus:
  • I’m intrigued by how you’ve employed innovative computational methods, including deep learning architectures like CVAE and CGGM, to target specific pathways. Could you share how this approach ensures selectivity without off-target interactions? What safety measures have been thoughtfully put in place? Furthermore, given the complex role of TGFß, how do you plan to prevent unintended consequences, like those related to cancer?

a. Selective multitargeting: both architectures use full proteome interaction targets that encode the desired binding of designed compounds for all (~22K) proteins. Typically we use the modeled interactions of an existing compound as a way to fill these interactions in as first approximation of the compound behavior we want to sample around. We then employ various proteomics and network analyses along with literature-identified targets to increase/decrease binding to specific proteins related to efficacy in the indication of choice—in this instance we intend to inhibit the TGFß pathway via direct binding and induce FGF21 through binding to repressive upstream proteins. Once a set of important proteins is identified, design is technically accomplished by modifying the appropriate binding scores in the objective interaction signature and letting the trained models convert this to compounds which will have the desired binding levels across the proteome. Through consensus proteomics approaches using the universe of approved drugs along with databases of proteins with documented implication in ADME/toxicity, we can similarly modify the objective interaction signature to account for off-target interactions. We ensure this behavior is actually preserved in the compounds we design by then modeling their interactions across the proteome and checking how similar these are to the objective interaction signature—by all accounts of benchmarking the design methods for redesigning existing drugs, i.e. creating structurally novel behavioral analogs, we see that our compounds exhibit the holistic and granular disease-implicated interactions we designed them to have.

b. Cancer/TGFß: A number of safety measures will be put in place during the design process to avoid potential adverse TGFß regulation and/or cancer. First, we are replicating the interactions of Reversine in initial programs, which when discovered as an aging/senescence intervention by our collaborator, Stelios Andreadis, had no signs of tumorigenic properties (Reversine has also found use in other literature as an anti-cancer/tumor compound). With respect to optimizing Reversine for TGFß signaling specifically, we can take additional measures tweaking the objective interaction signature to inhibit and/or avoid interaction with downstream oncogenic proteins drawn from literature/databases.

  1. Concerning Experimental Design, Validation, and Strategic Applications:
  • I’m eager to understand the careful planning that went into the experimental design. How did you define the key metrics for success in preclinical models, and what strategies were employed to harmonize the targeting studies? Also, could you shed light on how you chose the specific animal models for validation? I’m particularly curious about the potential of these compounds for diseases beyond progeria, and how you are leveraging progeria’s unique status in this context.

a. Proposed experiments: For the purposes of this proposal, senescence studies are the primary concern and were selected as an intuitive initial phenotypic screen for novel compounds designed for longevity in this proposal (as well as being the means through which Reversine was initially identified by our collaborator—keeping consistent with this). As far as actually measuring senescence, we selected a number of readouts that are generally gold-standard in the literature (p16 activity, SA-ß-gal, SASP) and give some additional information regarding the safety/relevance to aging hallmarks of delaying/reversing senescence, e.g. γH2AX for measuring DNA damage. As there is limited funding available, using this initial phenotypic screen to hone in on potential hits prior to focusing on proof of mechanism will be more efficient and align better with our holistic/proteomic approach to drug discovery.

b. Future experiments: no animal experiments are being proposed here for funding and any discussed in our slide deck are certainly subject to change as we raise additional funds and coordinate with experts; however, two mouse models will likely be explored for demonstrating progeria and longevity efficacy as these are also gold-standard for demonstrating holistic in vivo efficacy as well as confirming favorable ADME/toxicology profiles. We are leveraging progeria models simultaneous to aging as 1) there are several overlapping MoAs and phenotypic similarities between these indications and 2) as a strategic decision to reach the market faster through accelerated approval with successful leads.

3. Regarding IP, Regulatory, Commercialization Pathways, and Integration into the Longevity Research Landscape:

  • I’m sure that many of us would love to know more about the strategic planning behind the project. Could you give us some insight into your approach to intellectual property, international patents, and potential licensing? How are you navigating the complex regulatory landscape, especially concerning accelerated FDA approval? Moreover, how does your research fit into the broader longevity landscape, and what collaborations are you considering to enhance impact?

a. Intellectual property: Mansarover will license platform technology and subcontract initial experiments (budgeted for in the proposal) from the University at Buffalo. Chemical IP will be held by Mansarover as trade secrets during preclinical studies and protected under NDA/confidentiality agreements while working with external CROs (and UB). Following the identification of some set of clinical candidates we will seek IND filing and follow industry standards for subsequent CoM patent protection.

b. Regulatory landscape: Mansarover will follow the example set by Eiger Pharmaceuticals for seeking accelerated approval for Lonafarnib. I.e., we expect to obtain orphan status for compounds with efficacy in progeria models and will subsequently seek additional Priority, Breakthrough, and Rare Pediatric Disease designations by leveraging advantages we discover and intended broad anti-aging effects. Mansarover will seek simultaneous IND filing for these compounds in the context of the aging indication which will inherently require longer clinical studies. The purpose of designing compounds for progeria and longevity outcomes and the subsequent parallel approval pipeline is to reach the market sooner than other drugs only undergoing clinical aging studies to generate additional capital for ongoing studies, future programs, and early-investor incentives.

c. Broad landscape and collaborations: Our goals and methods align with several big players in the field now—most significantly, Ichor Life Sciences and Rejuvenate Bio. Ichor Life Sciences has invested in a number of anti-senescence programs and as of writing this, Mansarover is engaged in talks with Ichor officers with a formal pitch planned for early next month which will essentially increase the scale and scope of the studies proposed here. Ichor has thus far has informed experiment design and will provide additional expertise if an investment is established. On the other hand, Rejuvenate Bio is currently exploring gene therapies for FGF21/TGFß targeting in a similar fashion to the objectives proposed here. However, we are pursuing this in the context of small molecules which are generally easier to optimize deliverability/bioavailability for but have historically been difficult to design in a multitargeting context (which our platform solves for). Following initial phenotypic screens (senescence studies), and ADME/toxicology panels we will likely seek partners/perform additional fundraising for in vivo and clinical studies for which Rejuvenate Bio could be of potential support given alignment of goals.

2 Likes

Hi Shrike :wink: here are the answers from Brennan - let me know if you have any followup questions. Also, Brennan is preparing an updated proposal

I get told by my patent people that if it’s ‘obvious’, I can’t patent it. How would ‘like reversine but a little different’ end up being patentable?

Redesigns of Reversine (or any compound) resulting from our platform are achieved only by considering the compound’s interactions, i.e. no structural information is seen. Therefore, redesigns are entirely structurally novel (not merely iterations on functional groups etc, but typically entirely novel backbones/scaffolds) which mimic the behavior of Reversine (some with more favorable modeled interactions for longevity and some with less due to the generative nature of our methods). In the same way that there can exist two chemically distinct drugs that work through the same MoA, we can produce patentable redesigns of Reversine. With this in mind though, the true novelty/utility of our platform is optimizing these for additional aging mechanisms, i.e. TGFß and FGF21 so if we were to cut back on aims, so Aim 1b seems like the one to keep. And while we do not yet have wet-lab prelim data for this project, we do have some in silico on this which I plan to present tomorrow.

Proposed assays need to include viability. It’s not clear to me why you’d be using lentivirus for these assays. Are there more preliminary data showing the collaborator’s ability to measure senescence without lentivirus?

I may have submitted something more detailed in my initial funding application but for posterity, I attached a more substantial working technical/experimental plan that goes over the justifications for the readouts we’re looking at. If favorable to the Working Group, we can cut back on certain readouts but please let me know what you think. The broad goal/reason we’re proposing the experiments we do is to remain aligned with work our collaborator previously did to screen reversine (Reversine ameliorates hallmarks of cellular senescence in human skeletal myoblasts via reactivation of autophagy - PMC).

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Interesting concept. I need to look more closely. Worth going to diligence in my opinion.

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I updated the proposal addressing @bowtiedshrike’s and @vincent’s questions and concerns.

1 Like

@michele.gallia Thanks for the proposal. It’s a creative idea that has the right idea that we need to be hitting multiple pathways to significantly affect longevity.

Can you merge the new version into the old? it makes for a difficult to read thread to have both versions.

I like the small budget. This seems a good candidate for an IPNFT project. I have fairly significant concerns about whether the computational approach will achieve FGF21 upregulation and TGFB downregulation but I do think we have to try! Definitely need more computational efforts at VitaDAO. That being said, I echo @bowtiedshrike. Need some PoC that the this dual targeting is possible.

This project could use incubation, which makes it a good candidate for IPNFT. There’s been a wave of bifunctional/chimera chemistry building on protac example that could be considered. Both targets are extracellular so more elaborate chemistry could be contemplated because the drug won’t necessarily need to get into the cell.

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