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AlgenML: Drug target discovery platform for transcriptional reprogramming of MYCN-driven neuroblastoma

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R41GM146327-01
Agency Tracking Number: R41GM146327
Amount: $350,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: 400
Solicitation Number: PA20-265
Solicitation Year: 2020
Award Year: 2021
Award Start Date (Proposal Award Date): 2021-09-20
Award End Date (Contract End Date): 2022-08-31
Small Business Information
665 3RD ST STE 230
San Francisco, CA 94107-1954
United States
DUNS: 117063570
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 (408) 930-5704
Business Contact
Phone: (408) 930-5704
Research Institution
SAN FRANCISCO, CA 94143-2510
United States

 Nonprofit College or University

AlgenML: Drug target discovery platform for transcriptional reprogramming of MYCN-driven
Drug discovery is a laborious, time-consuming, and expensive undertaking for biopharma. Oncology is especially
difficult with new drugs in clinical trials having just 3.4% probability of success. This application addresses
significant challenges of traditional drug target discovery in oncology that relies on cell viability or reporter
assays which oversimplifies cell state. New advancements in single-cell RNA expression profiling allows us to
overcome these challenges by quantitatively mapping transcriptional dependencies in cancer cells and rapidly
probing vulnerabilities to reprogram the oncogenic signaling networks. Transcription factors MYCN and MYC are
to date non-druggable by small molecules despite being high value cancer drug targets as they are frequently
amplified genes and drive poor outcome across the cancer spectrum. Agents that block MYCN indirectly
identified from synthetic lethal viability screens have resulted in only modest or short-lived responses in ongoing
clinical trials. Algen’s proprietary machine learning platform (AlgenML) identifies targets that block oncogenic
transcription addiction on MYCN using single-cell RNA expression of CRISPR interference (CRISPRi) gene
knockdown. Genome-wide single-cell RNA expression profiling measures 10,000 genes per cell and each high-
throughput assay routinely captures 160,000 cells at once. Using CRISPRi gene knockdown libraries and
multiplexing the assays, hundreds of genes can be knocked down simultaneously and we single-cell RNA
sequence 200 cells per CRISPRi gene knockdown. This makes for an extremely rich data set with over 400
million data points of RNA expression data which AlgenML analyzes. Our drug discovery approach is innovative
because, unlike traditional approaches, the AlgenML platform does not identify essential genes that cause cell
death, but rather selects drug targets in an unbiased manner whose suppression can reprogram the disease-
related transcriptional dependencies. Resulting drugs should be safer and better tolerated. Here, our approach
is to optimize AlgenML to monitor and reprogram MYCN transcriptional activity in new genetically defined models
of MYCN-driven neuroblastoma. We focus on neuroblastoma because MYCN amplifications are common in the
disease, and the genetically defined models allow detection of the precise contribution of MYCN oncogene
compared to isogenic controls. In Aim 1, we define MYCN transcriptional signature, nominate target genes, and
test target genes in vitro based on their ability to reprogram the MYCN transcriptional dependency. Aim 2
evaluates in vivo efficacy of target inhibition to shrink tumors and extend lifespan in new human induced
pluripotent stem cell (iPSC) and rodent models of neuroblastoma from UCSF. Our team of investigators at
Algen and UCSF has decades of experience in developing RNA signatures to indirectly targeting MYC and
MYCN via synthetic lethality. Mature startup Algen Biotechnologies has a vibrant ecosystem of investors,
innovators, and grew out of Nobel Laureate Dr. Jennifer Doudna’s lab at UC Berkeley, who has been a scientific
advisor since its founding. With Dr. William Weiss at UCSF, we have assembled a powerhouse environment.PROJECT NARRATIVE
Algen is developing a drug discovery platform to select and test drug targets that block the oncogenic
transcriptional effects of non-druggable drivers such as MYCN. MYC and MYCN transcription factors
are directly non-druggable by small molecules, despite being high value targets for drug discovery
because their amplifications correlate with extremely poor prognosis across the cancer spectrum.
MYCN is amplified in 25% of all neuroblastoma, the most common extracranial solid tumor of childhood,
and marks high-risk disease with an aggressive phenotype that is resistant to chemotherapy and only
a 40-50% 5-year survival rate.

* Information listed above is at the time of submission. *

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