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2022 FDA Drug Approval List, 2022 Biological Approvals and Approved Cellular and Gene Therapy Products

Posted in cell-based therapy, Drug Discovery Chemistry, FDA, FDA, CE Mark & Global Regulatory Affairs: process management and strategic planning - GCP, GLP, ISO 14155, Pharmaceutical Discovery, Pharmaceutical Drug Discovery, Pharmaceutical R&D Informatics, Pharmacodynamics and Pharmacokinetics, Regenerative Biology and Medicine on January 17, 2023| Leave a Comment »

2022 FDA Drug Approval List, 2022 Biological Approvals and Approved Cellular and Gene Therapy Products

Reporter: Aviva Lev-Ari, PhD, RN

SOURCE

Tal Bahar’s post on LinkedIn on 1/17/2023

Novel Drug Approvals for 2022

FDA’s Center for Drug Evaluation and Research (CDER)

New Molecular Entities (“NMEs”)

  • Some of these products have never been used in clinical practice. Below is a listing of new molecular entities and new therapeutic biological products that CDER approved in 2022. This listing does not contain vaccines, allergenic products, blood and blood products, plasma derivatives, cellular and gene therapy products, or other products that the Center for Biologics Evaluation and Research approved in 2022. 
  • Others are the same as, or related to, previously approved products, and they will compete with those products in the marketplace. See Drugs@FDA for information about all of CDER’s approved drugs and biological products. 

Certain drugs are classified as new molecular entities (“NMEs”) for purposes of FDA review. Many of these products contain active moieties that FDA had not previously approved, either as a single ingredient drug or as part of a combination product. These products frequently provide important new therapies for patients. Some drugs are characterized as NMEs for administrative purposes, but nonetheless contain active moieties that are closely related to active moieties in products that FDA has previously approved. FDA’s classification of a drug as an “NME” for review purposes is distinct from FDA’s determination of whether a drug product is a “new chemical entity” or “NCE” within the meaning of the Federal Food, Drug, and Cosmetic Act. 

INNOVATION   PREDICTABILITY   ACCESS FDA’s Center for Drug Evaluation and Research

January 2023

Table of Contents

 SOURCE

2022 Biological Approvals

The Center for Biologics Evaluation and Research (CBER) regulates products under a variety of regulatory authorities.  See the Development & Approval Process page for a description of what products are approved as Biologics License Applications (BLAs), Premarket Approvals (PMAs), New Drug Applications (NDAs) or 510Ks.

Biologics License Applications and Supplements

New BLAs (except those for blood banking), and BLA supplements that are expected to significantly enhance the public health (e.g., for new/expanded indications, new routes of administration, new dosage formulations and improved safety).

Other Applications Approved or Cleared by the Center for Biologics Evaluation and Research (CBER)

Medical devices involved in the collection, processing, testing, manufacture and administration of licensed blood, blood components and cellular products.

Key Resources

SOURCE

https://www.fda.gov/vaccines-blood-biologics/development-approval-process-cber/2022-biological-approvals

 

Approved Cellular and Gene Therapy Products

Below is a list of licensed products from the Office of Tissues and Advanced Therapies (OTAT).

Approved Products

 

Resources For You

SOURCE

https://www.fda.gov/vaccines-blood-biologics/cellular-gene-therapy-products/approved-cellular-and-gene-therapy-products

 

2022 forecast: Cell, gene therapy makers push past regulatory, payer hurdles to set up high hopes for next year

By Arlene Weintraub
Dec 22, 2021 03:00am

There are five FDA-approved CAR-T treatments for blood cancers and two gene therapies to treat rare diseases now on the market in the U.S. The late-stage pipeline could produce several more cancer CAR-Ts and gene therapies to treat a range of diseases.

RELATED: ASH: Bristol Myers’ Breyanzi, Gilead’s Yescarta lock horns in race to move CAR-T therapy to earlier lymphoma

One of the biggest races to watch in the cell therapy space will be that between Gilead Sciences’ Yescarta and Bristol Myers Squibb’s Breyanzi, both of which are gunning to move their CAR-Ts into earlier lines of treatment in large B-cell lymphoma (LBCL). At ASH, both companies rolled out impressive data from their trials in the second-line setting, but Gilead could have the upper hand by virtue of its three-year head start in the market, analysts said. Gilead expects to hear from the FDA on a label expansion in the second-line setting in April.

SOURCE

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The drug efflux pump MDR1 promotes intrinsic and acquired resistance to PROTACs in cancer cells

Posted in CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Genomics, Cell Biology, Drug Development Process, Drug Discovery Chemistry, Genomic Expression, Loss of function gene, Metabolomics, Pharmaceutical Drug Discovery, tagged , , , , , , , , on October 11, 2022| Leave a Comment »

The drug efflux pump MDR1 promotes intrinsic and acquired resistance to PROTACs in cancer cells

Reporter: Stephen J. Williams, PhD.
Below is one of the first reports  on the potential mechanisms of intrinsic and acquired resistance to PROTAC therapy in cancer cells.
ALISON M. KURIMCHAK HTTPS://ORCID.ORG/0000-0003-2608-0128CARLOS HERRERA-MONTÁVEZSARA MONTSERRAT-SANGRÀDANIELA ARAIZA-OLIVERA HTTPS://ORCID.ORG/0000-0002-8207-9765JIANPING HU HTTPS://ORCID.ORG/0000-0002-6000-4922RYAN NEUMANN-DOMERMATHEW KURUVILLAALFONSO BELLACOSA HTTPS://ORCID.ORG/0000-0001-6278-6801JOSEPH R. TESTAJIAN JIN HTTPS://ORCID.ORG/0000-0002-2387-3862 AND JAMES S. DUNCAN 
Proteolysis-targeting chimeras (PROTACs) are a promising new class of drugs that selectively degrade cellular proteins of interest. PROTACs that target oncogene products are avidly being explored for cancer therapies, and several are currently in clinical trials. Drug resistance is a substantial challenge in clinical oncology, and resistance to PROTACs has been reported in several cancer cell models. Here, using proteomic analysis, we found intrinsic and acquired resistance mechanisms to PROTACs in cancer cell lines mediated by greater abundance or production of the drug efflux pump MDR1. PROTAC-resistant cells were resensitized to PROTACs by genetic ablation of ABCB1 (which encodes MDR1) or by coadministration of MDR1 inhibitors. In MDR1-overexpressing colorectal cancer cells, degraders targeting either the kinases MEK1/2 or the oncogenic mutant GTPase KRASG12C synergized with the dual epidermal growth factor receptor (EGFR/ErbB)/MDR1 inhibitor lapatinib. Moreover, compared with single-agent therapies, combining MEK1/2 degraders with lapatinib improved growth inhibition of MDR1-overexpressing KRAS-mutant colorectal cancer xenografts in mice. Together, our findings suggest that concurrent blockade of MDR1 will likely be required with PROTACs to achieve durable protein degradation and therapeutic response in cancer.

INTRODUCTION

Proteolysis-targeting chimeras (PROTACs) have emerged as a revolutionary new class of drugs that use cancer cells’ own protein destruction machinery to selectively degrade essential tumor drivers (1). PROTACs are small molecules with two functional ends, wherein one end binds to the protein of interest, whereas the other binds to an E3 ubiquitin ligase (2, 3), bringing the ubiquitin ligase to the target protein, leading to its ubiquitination and subsequent degradation by the proteasome. PROTACs have enabled the development of drugs against previously “undruggable” targets and require neither catalytic activity nor high-affinity target binding to achieve target degradation (4). In addition, low doses of PROTACs can be highly effective at inducing degradation, which can reduce off-target toxicity associated with high dosing of traditional inhibitors (3). PROTACs have been developed for a variety of cancer targets, including oncogenic kinases (5), epigenetic proteins (6), and, recently, KRASG12C proteins (7). PROTACs targeting the androgen receptor or estrogen receptor are avidly being evaluated in clinical trials for prostate cancer (NCT03888612) or breast cancer (NCT04072952), respectively.
However, PROTACs may not escape the overwhelming challenge of drug resistance that befalls so many cancer therapies (8). Resistance to PROTACs in cultured cells has been shown to involve genomic alterations in their E3 ligase targets, such as decreased expression of Cereblon (CRBN), Von Hippel Lindau (VHL), or Cullin2 (CUL2) (9–11). Up-regulation of the drug efflux pump encoded by ABCB1—MDR1 (multidrug resistance 1), a member of the superfamily of adenosine 5′-triphosphate (ATP)–binding cassette (ABC) transporters—has been shown to convey drug resistance to many anticancer drugs, including chemotherapy agents, kinase inhibitors, and other targeted agents (12). Recently, PROTACs were shown to be substrates for MDR1 (10, 13), suggesting that drug efflux represents a potential limitation for degrader therapies. Here, using degraders (PROTACs) against bromodomain and extraterminal (BET) bromodomain (BBD) proteins and cyclin-dependent kinase 9 (CDK9) as a proof of concept, we applied proteomics to define acquired resistance mechanisms to PROTAC therapies in cancer cells after chronic exposure. Our study reveals a role for the drug efflux pump MDR1 in both acquired and intrinsic resistance to protein degraders in cancer cells and supports combination therapies involving PROTACs and MDR1 inhibitors to achieve durable protein degradation and therapeutic responses.

Fig. 1. Proteomic characterization of degrader-resistant cancer cell lines.
(A) Workflow for identifying protein targets up-regulated in degrader-resistant cancer cells. Single-run proteome analysis was performed, and changes in protein levels among parent and resistant cells were determined by LFQ. m/z, mass/charge ratio. (B and C) Cell viability assessed by CellTiter-Glo in parental and dBET6- or Thal SNS 032–resistant A1847 cells treated with increasing doses of dBET6 (B) or Thal SNS 032 (C) for 5 days. Data were analyzed as % of DMSO control, presented as means ± SD of three independent assays. Growth inhibitory 50% (GI50) values were determined using Prism software. (D to G) Immunoblotting for degrader targets and downstream signaling in parental A1847 cells and their derivative dBET6-R or Thal-R cells treated with increasing doses of dBET6 or Thal SNS 032 for 4 hours. The dBET6-R and Thal-R cells were continuously cultured in 500 nM PROTAC. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 values, quantitating either (E) the dose of dBET6 that reduces BRD2, BRD3, or BRD4 or (G) the dose of Thal SNS 032 that reduces CDK9 protein levels 50% of the DMSO control treatment, were determined with Prism software. Pol II, polymerase II. (H to K) Volcano plot of proteins with increased or reduced abundance in dBET6-R (H) or Thal-R (I) A1847 cells relative to parental cells. Differences in protein log2 LFQ intensities among degrader-resistant and parental cells were determined by paired t test permutation-based adjusted P values at FDR of <0.05 using Perseus software. The top 10 up-regulated proteins in each are shown in (J) and (K), respectively. FC, fold change. (L and M) ABCB1 log2 LFQ values in dBET6-R cells from (H) and Thal-R cells from (I) compared with those in parental A1847 cells. Data are presented as means ± SD from three independent assays. By paired t test permutation-based adjusted P values at FDR of <0.05 using Perseus software, ***P ≤ 0.001. (N) Cell viability assessed by CellTiter-Glo in parental and MZ1-resistant SUM159 cells treated with increasing doses of MZ1 for 5 days. Data were analyzed as % of DMSO control, presented as means of three independent assays. GI50 values were determined using Prism software. (O and P) Immunoblotting for degrader targets and downstream signaling in parental or MZ1-R SUM159 cells treated with increasing doses of MZ1 for 24 hours. The MZ1-R cells were continuously cultured in 500 nM MZ1. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 values were determined in Prism software. (Q and R) Top 10 up-regulated proteins (Q) and ABCB1 log2 LFQ values (R) in MZ1-R cells relative to parental SUM159 cells

Fig. 2. Chronic exposure to degraders induces MDR1 expression and drug efflux activity.
(A) ABCB1 mRNA levels in parental and degrader-resistant cell lines as determined by qRT-PCR. Data are means ± SD of three independent experiments. ***P ≤ 0.001 by Student’s t test. (B) Immunoblot analysis of MDR1 protein levels in parental and degrader-resistant cell lines. Blots are representative of three independent experiments. (C to E) Immunofluorescence (“IF”) microscopy of MDR1 protein levels in A1847 dBET6-R (C), SUM159 MZ1-R (D), and Thal-R A1847 cells (E) relative to parental cells. Nuclear staining by DAPI. Images are representative of three independent experiments. Scale bars, 100 μm. (F) Drug efflux activity in A1847 dBET6-R, SUM159 MZ1-R, and Thal-R A1847 cells relative to parental cells (Par.) using rhodamine 123 efflux assays. Bars are means ± SD of three independent experiments. ***P ≤ 0.001 by Student’s t test. (G) Intracellular dBET6 levels in parental or dBET-R A1847 cells transfected with a CRBN sensor and treated with increasing concentrations of dBET6. Intracellular dBET6 levels measured using the CRBN NanoBRET target engagement assay. Data were analyzed as % of DMSO control, presented as means ± SD of three independent assays. *P ≤ 0.05, **P ≤ 0.01, and ***P ≤ 0.001 by Student’s t test. (H and I) FISH analysis of representative drug-sensitive parental and drug-resistant A1847 (H) and SUM159 (I) cells using ABCB1 and control XCE 7 centromere probes. Images of interphase nuclei were captured with a Metasystems Metafer microscope workstation, and the raw images were extracted and processed to depict ABCB1 signals in magenta, centromere 7 signals in cyan, and DAPI-stained nuclei in blue. (J and K) CpG methylation status of the ABCB1 downstream promoter (coordinates: chr7.87,600,166-87,601,336) by bisulfite amplicon sequencing in parent and degrader-resistant A1847 (J) and SUM159 (K) cells. Images depict the averaged percentage of methylation for each region of the promoter, where methylation status is depicted by color as follows: red, methylated; blue, unmethylated. Schematic of the ABCB1 gene with the location of individual CpG sites is shown. Graphs are representative of three independent experiments. (L and M) Immunoblot analysis of MDR1 protein levels after short-term exposure [for hours (h) or days (d) as indicated] to BET protein degraders dBET6 or MZ1 (100 nM) in A1847 (L) and SUM159 (M) cells, respectively. Blots are representative of three independent experiments. (N to P) Immunoblot analysis of MDR1 protein levels in A1847 and SUM159 cells after long-term exposure (7 to 30 days) to BET protein degraders dBET6 (N), Thal SNS 032 (O), or MZ1 (P), each at 500 nM. Blots are representative of three independent experiments. (Q and R) Immunoblot analysis of MDR1 protein levels in degrader-resistant A1847 (Q) and SUM159 (R) cells after PROTAC removal for 2 or 7 days. Blots are representative of three independent experiments.

 

Fig. 3. Blockade of MDR1 activity resensitizes degrader-resistant cells to PROTACs.
(A and B) Cell viability by CellTiter-Glo assay in parental and degrader-resistant A1847 (A) and SUM159 (B) cells transfected with control siRNA or siRNAs targeting ABCB1 and cultured for 120 hours. Data were analyzed as % of control, presented as means ± SD of three independent assays. ***P ≤ 0.001 by Student’s t test. (C and D) Immunoblot analysis of degrader targets after ABCB1 knockdown in parental and degrader-resistant A1847 (C) and SUM159 (D) cells. Blots are representative, and densitometric analyses using ImageJ are means ± SD of three blots, each normalized to the loading control, GAPDH. (E) Drug efflux activity, using the rhodamine 123 efflux assay, in degrader-resistant cells after MDR1 inhibition by tariquidar (0.1 μM). Data are means ± SD of three independent experiments. ***P ≤ 0.001 by Student’s t test. (F to H) Cell viability by CellTiter-Glo assay in parental and dBET6-R (F) or Thal-R (G) A1847 cells or MZ1-R SUM159 cells (H) treated with increasing concentrations of tariquidar. Data are % of DMSO control, presented as means ± SD of three independent assays. GI50 value determined with Prism software. (I to K) Immunoblot analysis of degrader targets after MDR1 inhibition (tariquidar, 0.1 μM for 24 hours) in parental and degrader-resistant A1847 cells (I and J) and SUM159 cells (K). Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. (L and M) A 14-day colony formation assessed by crystal violet staining of (L) A1847 cells or (M) SUM159 cells treated with degrader (0.1 μM; dBET6 or MZ1, respectively) and MDR1 inhibitor tariquidar (0.1 μM). Images are representative of three biological replicates. (N) Immunoblotting for MDR1 in SUM159 cells stably expressing FLAG-MDR1 after selection with hygromycin. (O) Long-term 14-day colony formation assay of SUM159 cells expressing FLAG-MDR1 that were treated with DMSO, MZ1 (0.1 μM), or MZ1 and tariquidar (0.1 μM) for 14 days, assessed by crystal violet staining. Representative images of three biological replicates are shown. (P and Q) RT-PCR (P) and immunoblot (Q) analysis of ABCB1 mRNA and MDR1 protein levels, respectively, in parental or MZ1-R HCT116, OVCAR3, and MOLT4 cells.

 

Fig. 4. Overexpression of MDR1 conveys intrinsic resistance to degrader therapies in cancer cells.
(A) Frequency of ABCB1 mRNA overexpression in a panel of cancer cell lines, obtained from cBioPortal for Cancer Genomics using Z-score values of >1.2 for ABCB1 mRNA levels (30). (B) Immunoblot for MDR1 protein levels in a panel of 10 cancer cell lines. Blots are representative of three independent experiments. (C) Cell viability by CellTiter-Glo assay in cancer cell lines expressing high or low MDR1 protein levels and treated with Thal SNS 032 for 5 days. Data were analyzed as % of DMSO control, presented as means ± SD of three independent assays. GI50 values were determined with Prism software. (D to F) Immunoblot analysis of CDK9 in MDR1-low (D) or MDR1-high (E) cell lines after Thal SNS 032 treatment for 4 hours. Blots are representative, and densitometric analyses using ImageJ are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value determined with Prism. (G and H) Immunoblotting of control and MDR1-knockdown DLD-1 cells treated for 4 hours with increasing concentrations of Thal SNS 032 [indicated in (H)]. Blots are representative, and densitometric analysis data are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value determined with Prism. (I) Drug efflux activity using rhodamine 123 efflux assays in DLD-1 cells treated with DMSO or 0.1 μM tariquidar. Data are means ± SD of three independent experiments. ***P ≤ 0.001 by Student’s t test. (J) Intracellular Thal SNS 032 levels, using the CRBN NanoBRET target engagement assay, in MDR1-overexpressing DLD-1 cells treated with DMSO or 0.1 μM tariquidar and increasing doses of Thal SNS 032. Data are % of DMSO control, presented as means ± SD of three independent assays. **P ≤ 0.01 and ***P ≤ 0.001 by Student’s t test. (K to N) Immunoblotting in DLD-1 cells treated with increasing doses of Thal SNS 032 (K and L) or dBET6 (M and N) alone or with tariquidar (0.1 μM) for 4 hours. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value of Thal SNS 032 for CDK9 reduction (L) or of dBET6 for BRD4 reduction (N) determined with Prism. (O to T) Bliss synergy scores based on cell viability by CellTiter-Glo assay, colony formation, and immunoblotting in DLD-1 cells treated with the indicated doses of Thal SNS 032 (O to Q) or dBET6 (R to T) alone or with tariquidar. Cells were treated for 14 days for colony formation assays and 24 hours for immunoblotting.

 

Fig. 5. Repurposing dual kinase/MDR1 inhibitors to overcome degrader resistance in cancer cells.
(A and B) Drug efflux activity by rhodamine 123 efflux assays in degrader-resistant [dBET-R (A) or Thal-R (B)] A1847 cells after treatment with tariquidar, RAD001, or lapatinib (each 2 μM). Data are means ± SD of three independent experiments. *P ≤ 0.05 by Student’s t test. (C and D) CellTiter-Glo assay for the cell viability of parental, dBET6-R, or Thal-R A1847 cells treated with increasing concentrations of RAD001 (C) or lapatinib (D). Data were analyzed as % of DMSO control, presented as means ± SD of three independent assays. GI50 values were determined with Prism software. (E to I) Immunoblot analysis of degrader targets in parental (E), dBET6-R (F and G), and Thal-R (H and I) A1847 cells treated with increasing concentrations of RAD001 or lapatinib for 4 hours. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value of dBET6 for BRD4 reduction (G) or of Thal SNS 032 for CDK9 reduction (I) determined with Prism. (J) Immunoblotting for cleaved PARP in dBET6-R or Thal-R A1847 cells treated with RAD001, lapatinib, or tariquidar (each 2 μM) for 24 hours. Blots are representative of three independent blots. (K to N) Immunoblotting for BRD4 in DLD-1 cells treated with increasing doses of dBET6 alone or in combination with either RAD001 or lapatinib [each 2 μM (K and L)] or KU-0063794 or afatinib [each 2 μM (M and N)] for 4 hours. Blots are representative of three independent experiments and, in (L), are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value for BRD4 reduction (L) determined in Prism. (O) Colony formation by DLD-1 cells treated with DMSO, dBET6 (0.1 μM), lapatinib (2 μM), afatinib (2 μM), RAD001 (2 μM), KU-0063794 (2 μM), or the combination of inhibitor and dBET6 for 14 days. Images representative of three independent assays. (P and Q) Immunoblotting for CDK9 in DLD-1 cells treated with increasing doses of Thal SNS 032 and/or RAD001 (2 μM) or lapatinib (2 μM) for 4 hours. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value for CDK9 reduction determined with Prism (Q). (R) Colony formation in DLD-1 cells treated with DMSO, Thal SNS 032 (0.5 μM), lapatinib (2 μM), and/or RAD001 (2 μM) as indicated for 14 days.

 

Fig. 6. Combining MEK1/2 degraders with lapatinib synergistically kills MDR1-overexpressing KRAS-mutant CRC cells and tumors.
(A and B) ABCB1 expression in KRAS-mutant CRC cell lines from cBioPortal (30) (A) and MDR1 abundance in select KRAS-mutant CRC cell lines (B). (C) Cell viability assessed by CellTiter-Glo in CRC cells treated with increasing doses of MS432 for 5 days, analyzed as % of DMSO control. GI50 value determined with Prism software. (D) Colony formation by CRC cells 14 days after treatment with 1 μM MS432. (E) MEK1/2 protein levels assessed by immunoblot in CRC lines SKCO1 (low MDR1) or LS513 (high MDR1) treated with increasing doses of MS432 for 4 hours. (F) Rhodamine 123 efflux in LS513 cells treated with DMSO, 2 μM tariquidar, or 2 μM lapatinib. (G and H) Immunoblotting analysis in LS513 cells treated with increasing doses of MS432 alone or in combination with tariquidar (0.1 μM) or lapatinib (5 μM) for 24 hours. DC50 value for MEK1 levels determined with Prism. (I) Immunoblotting in LS513 cells treated with DMSO, PD0325901 (0.01 μM), lapatinib (5 μM), or the combination for 48 hours. (J and K) Immunoblotting in LS513 cells treated either with DMSO, MS432 (1 μM), tariquidar (0.1 μM) (J), or lapatinib (5 μM) (K), alone or in combination. (L) Bliss synergy scores determined from cell viability assays (CellTiter-Glo) in LS513 cells treated with increasing concentrations of MS432, lapatinib, or the combination. (M and N) Colony formation by LS513 cells (M) and others (N) treated with DMSO, lapatinib (2 μM), MS432 (1 μM), or the combination for 14 days. (O and P) Immunoblotting in LS513 cells treated with increasing doses of MS934 alone (O) or combined with lapatinib (5 μM) (P) for 24 hours. (Q and R) Tumor volume of LS513 xenografts (Q) and the body weights of the tumor-bearing nude mice (R) treated with vehicle, MS934 (50 mg/kg), lapatinib (100 mg/kg), or the combination. n = 5 mice per treatment group. In (A) to (R), blots and images are representative of three independent experiments, and quantified data are means ± SD [SEM in (Q) and (R)] of three independent experiments; ***P ≤ 0.001 by Student’s t test.

 

Fig. 7. Lapatinib treatment improves KRASG12C degrader therapies in MDR1-overexpressing CRC cell lines.
(A and B) Colony formation by SW1463 (A) or SW837 (B) cells treated with DMSO, LC-2 (1 μM), or MRTX849 (1 μM) for 14 days. Images representative of three independent assays. (C to E) Immunoblotting in SW1463 cells (C and D) and SW837 cells (E) treated with DMSO, LC-2 (1 μM), tariquidar (0.1 μM) (C), or lapatinib (5 μM) (D and E) alone or in combination for 48 hours. Blots are representative of three independent experiments. (F and G) Bliss synergy scores based on CellTiter-Glo assay for the cell viability of SW1463 (F) or SW837 (G) cells treated with increasing concentrations of LC-2, lapatinib, or the combination. Data are means of three experiments ± SD. (H and I) Colony formation of SW1463 (H) or SW837 (I) cells treated as indicated (−, DMSO; LC-2, 1 μM; lapatinib, 2 μM; tariquidar, 0.1 μM) for 14 days. Images representative of three independent assays. (J) Rationale for combining lapatinib with MEK1/2 or KRASG12C degraders in MDR1-overexpressing CRC cell lines. Simultaneous blockade of MDR1 and ErbB receptor signaling overcomes degrader resistance and ErbB receptor kinome reprogramming, resulting in sustained inhibition of KRAS effector signaling.

SOURCE

Other articles in this Open Access Scientific Journal on PROTAC therapy in cancer include

Accelerating PROTAC drug discovery: Establishing a relationship between ubiquitination and target protein degradation

The Vibrant Philly Biotech Scene: Proteovant Therapeutics Using Artificial Intelligence and Machine Learning to Develop PROTACs

The Map of human proteins drawn by artificial intelligence and PROTAC (proteolysis targeting chimeras) Technology for Drug Discovery

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AI enabled Drug Discovery and Development: The Challenges and the Promise

Posted in Artificial Intelligence Applications in Health Care, Artificial Intelligence in Health Care - Tools & Innovations, Artificial Intelligence in Medicine - Applications in Therapeutics, Drug Development Process, Drug Discovery Chemistry, Machine Learning, Pharmaceutical Drug Discovery, Pharmaceutical Industry Competitive Intelligence, Pharmacogenomics on March 18, 2022| 1 Comment »

AI enabled Drug Discovery and Development: The Challenges and the Promise

Reporter: Aviva Lev-Ari, PhD, RN

 

Early Development

Caroline Kovac (the first IBM GM of Life Sciences) is the one who started in silico development of drugs in 2000 using a big db of substances and computer power. She transformed an idea into $2b business. Most of the money was from big pharma. She was asking what is are the new drugs they are planning to develop and provided the four most probable combinations of substances, based on in Silicon work. 

Carol Kovac

General Manager, Healthcare and Life Sciences, IBM

from speaker at conference on 2005

Carol Kovac is General Manager of IBM Healthcare and Life Sciences responsible for the strategic direction of IBM′s global healthcare and life sciences business. Kovac leads her team in developing the latest information technology solutions and services, establishing partnerships and overseeing IBM investment within the healthcare, pharmaceutical and life sciences markets. Starting with only two employees as an emerging business unit in the year 2000, Kovac has successfully grown the life sciences business unit into a multi-billion dollar business and one of IBM′s most successful ventures to date with more than 1500 employees worldwide. Kovac′s prior positions include general manager of IBM Life Sciences, vice president of Technical Strategy and Division Operations, and vice president of Services and Solutions. In the latter role, she was instrumental in launching the Computational Biology Center at IBM Research. Kovac sits on the Board of Directors of Research!America and Africa Harvest. She was inducted into the Women in Technology International Hall of Fame in 2002, and in 2004, Fortune magazine named her one of the 50 most powerful women in business. Kovac earned her Ph.D. in chemistry at the University of Southern California.

SOURCE

https://www.milkeninstitute.org/events/conferences/global-conference/2005/speaker-detail/1536

 

In 2022

The use of artificial intelligence in drug discovery, when coupled with new genetic insights and the increase of patient medical data of the last decade, has the potential to bring novel medicines to patients more efficiently and more predictably.

WATCH VIDEO

https://www.youtube.com/watch?v=b7N3ijnv6lk

SOURCE

https://engineering.stanford.edu/magazine/promise-and-challenges-relying-ai-drug-development?utm_source=Stanford+ALL

Conversation among three experts:

Jack Fuchs, MBA ’91, an adjunct lecturer who teaches “Principled Entrepreneurial Decisions” at Stanford School of Engineering, moderated and explored how clearly articulated principles can guide the direction of technological advancements like AI-enabled drug discovery.

Kim Branson, Global head of AI and machine learning at GSK.

Russ Altman, the Kenneth Fong Professor of Bioengineering, of genetics, of medicine (general medical discipline), of biomedical data science and, by courtesy, of computer science.

 

Synthetic Biology Software applied to development of Galectins Inhibitors at LPBI Group

https://pharmaceuticalintelligence.com/synthetic-biology-in-drug-discovery/

 

The Map of human proteins drawn by artificial intelligence and PROTAC (proteolysis targeting chimeras) Technology for Drug Discovery

Curators: Dr. Stephen J. Williams and Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2021/10/21/the-map-of-human-proteins-drawn-by-artificial-intelligence-and-protac-proteolysis-targeting-chimeras-technology-for-drug-discovery/

Using Structural Computation Models to Predict Productive PROTAC Ternary Complexes

Ternary complex formation is necessary but not sufficient for target protein degradation. In this research, Bai et al. have addressed questions to better understand the rate-limiting steps between ternary complex formation and target protein degradation. They have developed a structure-based computer model approach to predict the efficiency and sites of target protein ubiquitination by CRNB-binding PROTACs. Such models will allow a more complete understanding of PROTAC-directed degradation and allow crafting of increasingly effective and specific PROTACs for therapeutic applications.

Another major feature of this research is that it a result of collaboration between research groups at Amgen, Inc. and Promega Corporation. In the past commercial research laboratories have shied away from collaboration, but the last several years have found researchers more open to collaborative work. This increased collaboration allows scientists to bring their different expertise to a problem or question and speed up discovery. According to Dr. Kristin Riching, Senior Research Scientist at Promega Corporation, “Targeted protein degraders have broken many of the rules that have guided traditional drug development, but it is exciting to see how the collective learnings we gain from their study can aid the advancement of this new class of molecules to the clinic as effective therapeutics.”

Literature Reviewed

Bai, N. , Riching K.M. et al. (2022) Modeling the CRLRA ligase complex to predict target protein ubiquitination induced by cereblon-recruiting PROTACs. J. Biol. Chem.

The researchers NanoBRET assays as part of their model validation. Learn more about NanoBRET technology at the Promega.com website.

SOURCE

https://www.promegaconnections.com/protac-ternary-complex/?utm_campaign=ms-2022-pharma_tpd&utm_source=linkedin&utm_medium=Khoros&utm_term=sf254230485&utm_content=030822ct-blogsf254230485&sf254230485=1

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A laboratory for the use of AI for drug development has been launched in collaboration with Pfizer, Teva, AstraZeneca, Mark and Amazon

Posted in Artificial Intelligence in Medicine - Applications in Therapeutics, Disease Biology, Drug Discovery Chemistry, Machine Learning, Pharmaceutical Discovery, Pharmaceutical Drug Discovery, Pharmaceutical Industry Competitive Intelligence, Technology Transfer: Biotech and Pharmaceutical on October 16, 2021| Leave a Comment »

A laboratory for the use of AI for drug development has been launched in collaboration with Pfizer, Teva, AstraZeneca, Mark and Amazon

Reporter: Aviva Lev-Ari, PhD, RN

AION Labs unites pharma, technology and funds companies including IBF to invest in startups to integrate developments in cloud computing and artificial intelligence to improve drug development capabilities. An alliance of four leading pharmaceutical companies –  
AION Labs , the first innovation lab of its kind in the world and a pioneer in the process of adopting cloud technologies, artificial intelligence and computer science to solve the R&D challenges of the pharma industry, today announces its launch.
AstraZeneca ,  
Mark ,  
Pfizer  and 
Teva  – and two leading companies in the field of high-tech and biotech investments, respectively – AWS ( 
Amazon Web Services Inc ) and the Israeli investment fund IBF ( 
Israel Biotech Fund ) – which joined together to establish groundbreaking ventures Through artificial intelligence and computer science to change the way new therapies are discovered and developed.  “We are excited to launch the new innovation lab in favor of discoveries of drugs and medical devices using groundbreaking computational tools,” said Matti Gil, CEO of AION Labs. We are prepared and ready to make a difference in the process of therapeutic discoveries and their development. 
With a strong pool of talent from Israel and the world, cloud technology and artificial intelligence at the heart of our activities and a significant commitment by the State of Israel, we are ready to contribute to the health and well-being of the human race and promote industry in Israel. 
I thank the partners for the trust, and it is an honor for me to lead such a significant initiative. ” 
In addition, AION Labs has announced a strategic partnership with X  
BioMed  , an independent biomedical research institute operating in Heidelberg, Germany. 
BioMed X has a proven track record in advancing research innovations in the field of biomedicine at the interface between academic research and the pharmaceutical industry. 
BioMed X’s innovation model, based on global mass sourcing and incubators to cultivate the most brilliant talent and ideas, will serve as the R & D engine to drive AION Labs’ enterprise model.

SOURCE

הושקה מעבדה לשימוש ב-AI לפיתוח תרופות בשיתוף פייזר, טבע, אסטרהזנקה, מרק ואמזון

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A Platform called VirtualFlow: Discovery of Pan-coronavirus Drugs help prepare the US for the Next Coronavirus Pandemic

Posted in COVID-19, Drug Discovery Chemistry, Mechanisms of infection by SARS-CoV-2, Pharmaceutical Analytics, Pharmaceutical Discovery, Pharmaceutical Drug Discovery, Pharmaceutical R&D Informatics, Pharmaceutical R&D Investment, Population Health Management, Genetics & Pharmaceutical, SARS-CoV-2, Virtual Drug Molecule Screening targeting SAR-CoV-2 proteins, Virus Infective Acute Respiratory Syndrome: SARS-CoV on February 1, 2021| Leave a Comment »

A Platform called VirtualFlow: Discovery of Pan-coronavirus Drugs help prepare the US for the Next Coronavirus Pandemic

Reporter: Aviva Lev-Ari, PhD, RN

 

ARTICLE|ONLINE NOW, 102021

A multi-pronged approach targeting SARS-CoV-2 proteins using ultra-large virtual screening

Open AccessPublished:January 04, 2021DOI:https://doi.org/10.1016/j.isci.2020.102021

SOURCE

https://www.cell.com/iscience/fulltext/S2589-0042(20)31218-9

 

The work was made possible in large part by about $1 million in cloud computing hours awarded by Google through a COVID-19 research grant program.

The work reported, below was sponsored by

  • a Google Cloud COVID-19 research grant. Funding was also provided by the
  • Fondation Aclon,
  • National Institutes of Health (GM136859),
  • Claudia Adams Barr Program for Innovative Basic Cancer Research,
  • Math+ Berlin Mathematics Research Center,
  • Templeton Religion Trust (TRT 0159),
  • U.S. Army Research Office (W911NF1910302), and
  • Chleck Family Foundation

 

Harvard University, AbbVie form research alliance to address emergent viral diseases

 Research

This article is part of Harvard Medical School’s continuing coverage of medicine, biomedical research, medical education and policy related to the SARS-CoV-2 pandemic and the disease COVID-19.

Harvard University and AbbVie today announced a $30 million collaborative research alliance, launching a multi-pronged effort at Harvard Medical School to study and develop therapies against emergent viral infections, with a focus on those caused by coronaviruses and by viruses that lead to hemorrhagic fever.

The collaboration aims to rapidly integrate fundamental biology into the preclinical and clinical development of new therapies for viral diseases that address a variety of therapeutic modalities. HMS has led several large-scale, coordinated research efforts launched at the beginning of the COVID-19 pandemic.

“A key element of having a strong R&D organization is collaboration with top academic institutions, like Harvard Medical School, to develop therapies for patients who need them most,” said Michael Severino, vice chairman and president of AbbVie. “There is much to learn about viral diseases and the best way to treat them. By harnessing the power of collaboration, we can develop new therapeutics sooner to ensure the world is better prepared for future potential outbreaks.”

“The cataclysmic nature of the COVID-19 pandemic reminds us how vital it is to be prepared for the next public health crisis and how critical collaboration is on every level—across disciplines, across institutions and across national boundaries,” said George Q. Daley, dean of Harvard Medical School. “Harvard Medical School, as the nucleus of an ecosystem of fundamental discovery and therapeutic translation, is uniquely positioned to propel this transformative research alongside allies like AbbVie.”

AbbVie will provide $30 million over three years and additional in-kind support leveraging AbbVie’s scientists, expertise and facilities to advance collaborative research and early-stage development efforts across five program areas that address a variety of therapeutic modalities:

  • Immunity and immunopathology—Study of the fundamental processes that impact the body’s critical immune responses to viruses and identification of opportunities for therapeutic intervention.

Led by Ulirich Von Andrian, the Edward Mallinckrodt Jr. Professor of Immunopathology in the Blavatnik Institute at HMS and program leader of basic immunology at the Ragon Institute of MGH, MIT and Harvard, and Jochen Salfeld, vice president of immunology and virology discovery at AbbVie.

  • Host targeting for antiviral therapies—Development of approaches that modulate host proteins in an effort to disrupt the life cycle of emergent viral pathogens.

Led by Pamela Silver, the Elliot T. and Onie H. Adams Professor of Biochemistry and Systems Biology in the Blavatnik Institute at HMS, and Steve Elmore, vice president of drug discovery science and technology at AbbVie.

  • Antibody therapeutics—Rapid development of therapeutic antibodies or biologics against emergent pathogens, including SARS-CoV-2, to a preclinical or early clinical stage.

Led by Jonathan Abraham, assistant professor of microbiology in the Blavatnik Institute at HMS, and by Jochen Salfeld, vice president of immunology and virology discovery at AbbVie.

  • Small molecules—Discovery and early-stage development of small-molecule drugs that would act to prevent replication of known coronaviruses and emergent pathogens.

Led by Mark Namchuk, executive director of therapeutics translation at HMS and senior lecturer on biological chemistry and molecular pharmacology in the Blavatnik Institute at HMS, and Steve Elmore, vice president of drug discovery science and technology at AbbVie.

  • Translational development—Preclinical validation, pharmacological testing, and optimization of leading approaches, in collaboration with Harvard-affiliated hospitals, with program leads to be determined.

SOURCE

https://hms.harvard.edu/news/joining-forces

 

 

A Screen Door Opens

Virtual screen finds compounds that could combat SARS-CoV-2

By STEPHANIE DUTCHEN  Research

This article is part of Harvard Medical School’s continuing coverage of medicine, biomedical research, medical education, and policy related to the SARS-CoV-2 pandemic and the disease COVID-19.

Less than a year ago, Harvard Medical School researchers and international colleagues unveiled a platform called VirtualFlow that could swiftly sift through more than 1 billion chemical compounds and identify those with the greatest promise to become disease-specific treatments, providing researchers with invaluable guidance before they embark on expensive and time-consuming lab experiments and clinical trials.

Propelled by the urgent needs of the pandemic, the team has now pushed VirtualFlow even further, conducting 45 screens of more than 1 billion compounds each and ranking the compounds with the greatest potential for fighting COVID-19—including some that are already approved by the FDA for other diseases.

“This was the largest virtual screening effort ever done,” said VirtualFlow co-developer Christoph Gorgulla, research fellow in biological chemistry and molecular pharmacology in the labs of Haribabu Arthanari and Gerhard Wagner in the Blavatnik Institute at HMS.

The results were published in January in the open-access journal iScience.

The team searched for compounds that bind to any of 15 proteins on SARS-CoV-2 or two human proteins, ACE2 and TMPRSS2, known to interact with the virus and enable infection.

Researchers can now explore on an interactive website the 1,000 most promising compounds from each screen and start testing in the lab any ones they choose.

The urgency of the pandemic and the sheer number of candidate compounds inspired the team to release the early results to the scientific community.

“No one group can validate all the compounds as quickly as the pandemic demands,” said Gorgulla, who is also an associate of the Department of Physics at Harvard University. “We hope that our colleagues can collectively use our results to identify potent inhibitors of SARS-CoV-2.”

In most cases, it will take years to find out whether a compound is safe and effective in humans. For some of the compounds, however, researchers have a head start.

Hundreds of the most promising compounds that VirtualFlow flagged are already FDA approved or being studied in clinical or preclinical trials for other diseases. If researchers find that one of those compounds proves effective against SARS-CoV-2 in lab experiments, the data their colleagues have already collected could save time establishing safety in humans.

Other compounds among VirtualFlow’s top hits are currently being assessed in clinical trials for COVID-19, including several drugs in the steroid family. In those cases, researchers could build on the software findings to investigate how those drug candidates work at the molecular level—something that’s not always clear even when a drug works well.

It shows what we’re capable of computationally during a pandemic.

Hari Arthanari

In another effort to speed successful transitions from computer to clinic, the team has joined in Harvard’s partnership with pharmaceutical company AbbVie.

If any successful drugs eventually arise from the VirtualFlow screens, they would complement other strategies in the fight against COVID-19. For instance, drugs that halt viral replication or prevent it from entering cells could help those who cannot be vaccinated.

The nature of the screens also raises the likelihood that drugs developed against current forms of SARS-CoV-2 would work against future mutations or other coronaviruses, the authors say.

Computing power

The work was made possible in large part by about $1 million in cloud computing hours awarded by Google through a COVID-19 research grant program.

Gorgulla and colleagues used that power to screen how well the compounds bound to more than 40 sites across the 15 viral proteins as well as to the two human proteins—effectively trying 1 billion 3D puzzle pieces in 40 places each.

The team selected the sites because blocking them with compounds would either prevent SARS-CoV-2 from entering cells, prevent the virus from replicating and thus lower viral load, reduce the virus’s ability to evade or subvert our immune defenses, or disrupt viral assembly and packaging.

Many of the sites have not yet been investigated by other groups, as far as the team is aware.

“We’re exploring new avenues on how to tackle the virus. This is one of the most exciting aspects of our project,” said Gorgulla.

One benefit of studying dozens of sites on 17 proteins at once is the possibility of identifying or developing multiple drugs that, when combined, combat SARS-CoV-2 infection on different fronts. Such drug cocktails would have a better chance of halting the virus in its tracks and overcoming future mutations than a single drug that works on one protein site.

Some sites included in the screen are shared among other coronaviruses of worldwide concern. Any compound that binds to one of those sites has a “high” chance of also combating SARS, MERS, or as-yet-unknown coronavirus diseases, said Arthanari.

“We are in a position to discover pan-coronavirus drugs and help prepare for the next coronavirus pandemic, should there ever be one,” said Gorgulla.

Regardless of the outcomes, the work raises the benchmark for virtual screening and demonstrates the current power of computing in biological research.

“It shows what we’re capable of computationally during a pandemic,” said Arthanari.

The project has also brought special satisfaction to team members who don’t typically work on projects so closely tied to human health.

SOURCE

https://hms.harvard.edu/news/screen-door-opens?utm_source=Silverpop&utm_medium=email&utm_term=field_news_item_1&utm_content=HMNews02012021

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The Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Partnership on May 18, 2020

Posted in Coronavirus Gene Expression, COVID-19, Drug Development Process, Drug Discovery Chemistry, drug repurposing, Personal Health Applications: Tech Innovations serves HealhCare, Personalized and Precision Medicine & Genomic Research, Pharmaceutical Discovery, Pharmaceutical Drug Discovery, Pharmaceutical Industry Competitive Intelligence, Pharmaceutical R&D Informatics, Pharmaceutical R&D Investment, Pharmacogenomics, Pharmacovigilance, Population Health Management, Population Health Management, Genetics & Pharmaceutical, SARS-CoV-2, Serology tests for coronavirus antibodies, Vaccinology, Virus Infective Acute Respiratory Syndrome: SARS-CoV on May 18, 2020| Leave a Comment »

The Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Partnership on May 18, 2020: Leadership of AbbVie, Amgen, AstraZeneca, Bristol Myers Squibb, Eisai, Eli Lilly, Evotec, Gilead, GlaxoSmithKline, Johnson & Johnson, KSQ Therapeutics, Merck, Novartis, Pfizer, Roche, Sanofi, Takeda, and Vir. We also thank multiple NIH institutes (especially NIAID), the FDA, BARDA, CDC, the European Medicines Agency, the Department of Defense, the VA, and the Foundation for NIH

Reporter: Aviva Lev-Ari, PhD, RN

May 18, 2020

Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) An Unprecedented Partnership for Unprecedented Times

Francis S. Collins, MD, PhD1; Paul Stoffels, MD2
Article Information
JAMA. Published online May 18, 2020. doi:10.1001/jama.2020.8920
Author Affiliations

  • 1Office of the Director, National Institutes of Health, Bethesda, Maryland
  • 2Johnson & Johnson, New Brunswick, New Jersey

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It has been more than a century since the world has encountered a pandemic like coronavirus disease 2019 (COVID-19), and the rate of spread of COVID-19 around the globe and the associated morbidity and mortality have been staggering.1 To address what may be the greatest public health crisis of this generation, it is imperative that all sectors of society work together in unprecedented ways, with unprecedented speed. In this Viewpoint, we describe such a partnership.

First reported in Wuhan, China, in December 2019, COVID-19 is caused by a highly transmissible novel coronavirus, SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). By March 2020, as COVID-19 moved rapidly throughout Europe and the US, most researchers and regulators from around the world agreed that it would be necessary to go beyond “business as usual” to contain this formidable infectious agent. The biomedical research enterprise was more than willing to respond to the challenge of COVID-19, but it soon became apparent that much-needed coordination among important constituencies was lacking.

Clinical trials of investigational vaccines began as early as January, but with the earliest possible distribution predicted to be 12 to 18 months away. Clinical trials of experimental therapies had also been initiated, but most, except for a trial testing the antiviral drug remdesivir,2 were small and not randomized. In the US, there was no true overarching national process in either the public or private sector to prioritize candidate therapeutic agents or vaccines, and no efforts were underway to develop a clear inventory of clinical trial capacity that could be brought to bear on this public health emergency. Many key factors had to change if COVID-19 was to be addressed effectively in a relatively short time frame.

On April 3, leaders of the National Institutes of Health (NIH), with coordination by the Foundation for the National Institutes of Health (FNIH), met with multiple leaders of research and development from biopharmaceutical firms, along with leaders of the US Food and Drug Administration (FDA), the Biomedical Advanced Research and Development Authority (BARDA), the European Medicines Agency (EMA), and academic experts. Participants sought urgently to identify research gaps and to discuss opportunities to collaborate in an accelerated fashion to address the complex challenges of COVID-19.

These critical discussions culminated in a decision to form a public-private partnership to focus on speeding the development and deployment of therapeutics and vaccines for COVID-19. The group assembled 4 working groups to focus on preclinical therapeutics, clinical therapeutics, clinical trial capacity, and vaccines (Figure). In addition to the founding members, the working groups’ membership consisted of senior scientists from each company or agency, the Centers for Disease Control and Prevention (CDC), the Department of Veterans Affairs (VA), and the Department of Defense.

Figure.

Accelerating COVID-19 Therapeutic Interventions and Vaccines

ACTIV’s 4 working groups, each with one cochair from NIH and one from industry, have made rapid progress in establishing goals, setting timetables, and forming subgroups focused on specific issues (Figure). The goals of the working group, along with a few examples of their accomplishments to date, include the following.

 

The Preclinical Working Group was charged to standardize and share preclinical evaluation resources and methods and accelerate testing of candidate therapies and vaccines to support entry into clinical trials. The aim is to increase access to validated animal models and to enhance comparison of approaches to identify informative assays. For example, through the ACTIV partnership, this group aims to extend preclinical researchers’ access to high-throughput screening systems, especially those located in the Biosafety Level 3 (BSL3) facilities currently required for many SARS-CoV-2 studies. This group also is defining a prioritization approach for animal use, assay selection and staging of testing, as well as completing an inventory of animal models, assays, and BSL 3/4 facilities.

 

The Therapeutics Clinical Working Group has been charged to prioritize and accelerate clinical evaluation of a long list of therapeutic candidates for COVID-19 with near-term potential. The goals have been to prioritize and test potential therapeutic agents for COVID-19 that have already been in human clinical trials. These may include agents with either direct-acting or host-directed antiviral activity, including immunomodulators, severe symptom modulators, neutralizing antibodies, or vaccines. To help achieve these goals, the group has established a steering committee with relevant expertise and objectivity to set criteria for evaluating and ranking potential candidate therapies submitted by industry partners. Following a rigorous scientific review, the prioritization subgroup has developed a complete inventory of approximately 170 already identified therapeutic candidates that have acceptable safety profiles and different mechanisms of action. On May 6, the group presented its first list of repurposed agents recommended for inclusion in ACTIV’s master protocol for adaptive clinical trials. Of the 39 agents that underwent final prioritization review, the group identified 6 agents—including immunomodulators and supportive therapies—that it proposes to move forward into the master protocol clinical trial(s) expected to begin later in May.

 

The Clinical Trial Capacity Working Group is charged with assembling and coordinating existing networks of clinical trials to increase efficiency and build capacity. This will include developing an inventory of clinical trial networks supported by NIH and other funders in the public and private sectors, including contract research organizations. For each network, the working group seeks to identify their specialization in different populations and disease stages to leverage infrastructure and expertise from across multiple networks, and establish a coordination mechanism across networks to expedite trials, track incidence across sites, and project future capacity. The clinical trials inventory subgroup has already identified 44 networks, with access to adult populations and within domestic reach, for potential inclusion in COVID-19 trials. Meanwhile, the survey subgroup has developed 2 survey instruments to assess the capabilities and capacities of those networks, and its innovation subgroup has developed a matrix to guide deployment of innovative solutions throughout the trial life cycle.

 

The Vaccines Working Group has been charged to accelerate evaluation of vaccine candidates to enable rapid authorization or approval.4 This includes development of a harmonized master protocol for adaptive trials of multiple vaccines, as well as development of a trial network that could enroll as many as 100 000 volunteers in areas where COVID-19 is actively circulating. The group also aims to identify biomarkers to speed authorization or approval and to provide evidence to address cross-cutting safety concerns, such as immune enhancement. Multiple vaccine candidates will be evaluated, and the most promising will move to a phase 2/3 adaptive trial platform utilizing large geographic networks in the US and globally.5 Because time is of the essence, ACTIV will aim to have the next vaccine candidates ready to enter clinical trials by July 1, 2020.

References

1.

Desai  A .  Twentieth-century lessons for a modern coronavirus pandemic.   JAMA. Published online April 27, 2020. doi:10.1001/jama.2020.4165
ArticlePubMedGoogle Scholar

2.

NIH clinical trial shows remdesivir accelerates recovery from advanced COVID-19. National Institutes of Health. Published April 29, 2020. Accessed May 7, 2020. https://www.nih.gov/news-events/news-releases/nih-clinical-trial-shows-remdesivir-accelerates-recovery-advanced-covid-19

3.

NIH to launch public-private partnership to speed COVID-19 vaccine and treatment options. National Institutes of Health. Published April 17, 2020. Accessed May 7, 2020. https://www.nih.gov/news-events/news-releases/nih-launch-public-private-partnership-speed-covid-19-vaccine-treatment-options

4.

Corey  L , Mascola  JR , Fauci  AS , Collins  FS .  A strategic approach to COVID-19 vaccine R&D.   Science. Published online May 11, 2020. doi:10.1126/science.abc5312PubMedGoogle Scholar

5.

Angus  DC .  Optimizing the trade-off between learning and doing in a pandemic.   JAMA. Published online March 30, 2020. doi:10.1001/jama.2020.4984
ArticlePubMedGoogle Scholar

6.

Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) portal. National Institutes of Health. Accessed May 15, 2020. https://www.nih.gov/ACTIV

7.

Accelerating Medicines Partnership (AMP). National Institutes of Health. Published February 4, 2014. Accessed May 7, 2020. https://www.nih.gov/research-training/accelerating-medicines-partnership-amp
SOURCE

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Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 27, 2020 Opening Remarks and Clinical Session 11:45am-1:15pm Advances in Cancer Drug Discovery

Posted in Cancer - General, Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Conference Coverage with Social Media, Curation, Drug Delivery Platform Technology, Drug Development Process, Drug Discovery Chemistry, Pharmaceutical Drug Discovery, Pharmaceutical Industry Competitive Intelligence, Pharmaceutical R&D Investment, Pharmacodynamics and Pharmacokinetics, REAL TIME Conference Coverage Twitter's Hashtags and Handles per Presentation/session, Scientific & Biotech Conferences: Press Coverage, Small Molecules in Development of Therapeutic Drugs, tagged , , , , , , , , , , on April 27, 2020| Leave a Comment »

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 27, 2020 Opening Remarks and Clinical Session 11:45am-1:15pm Advances in Cancer Drug Discovery

SESSION VMS.CH01.01 – Advances in Cancer Drug Design and Discovery

April 27, 2020, 11:45 AM – 1:15 PM
Virtual Meeting: All Session Times Are U.S. EDT
DESCRIPTIONAll session times are U.S. Eastern Daylight Time (EDT).

Session Type
Virtual Minisymposium
Track(s)
Cancer Chemistry
14 Presentations
11:45 AM – 11:45 AM
– ChairpersonZoran Rankovic. St. Jude Children’s Research Hospital, Memphis, TN

11:45 AM – 11:45 AM
– ChairpersonChristopher G. Nasveschuk. C4 Therapeutics, Watertown, MA

11:45 AM – 11:50 AM
– IntroductionZoran Rankovic. St. Jude Children’s Research Hospital, Memphis, TN

11:50 AM – 12:00 PM
1036 – Discovery of a highly potent, efficacious and orally active small-molecule inhibitor of embryonic ectoderm development (EED)Changwei Wang, Rohan Kalyan Rej, Jianfeng Lu, Mi Wang, Kaitlin P. Harvey, Chao-Yie Yang, Ester Fernandez-Salas, Jeanne Stuckey, Elyse Petrunak, Caroline Foster, Yunlong Zhou, Rubin Zhou, Guozhi Tang, Jianyong Chen, Shaomeng Wang. Rogel Cancer Center and Departments of Internal Medicine, Pharmacology, and Medicinal Chemistry, Life Sciences Institute, University of Michigan, Ann Arbor, MI, Ascentage Pharma Group, Taizhou, Jiangsu, China

12:00 PM – 12:05 PM
– Discussion

12:05 PM – 12:15 PM
1037 – Orally available small molecule CD73 inhibitor reverses immunosuppression through blocking of adenosine productionXiaohui Du, Brian Blank, Brenda Chan, Xi Chen, Yuping Chen, Frank Duong, Lori Friedman, Tom Huang, Melissa R. Junttila, Wayne Kong, Todd Metzger, Jared Moore, Daqing Sun, Jessica Sun, Dena Sutimantanapi, Natalie Yuen, Tatiana Zavorotinskaya. ORIC Pharmaceuticals, South San Francisco, CA, ORIC Pharmaceuticals, South San Francisco, CA, ORIC Pharmaceuticals, South San Francisco, CA, ORIC Pharmaceuticals, South San Francisco, CA

12:15 PM – 12:20 PM
– Discussion

12:20 PM – 12:30 PM
1038 – A potent and selective PARP14 inhibitor decreases pro-tumor macrophage function and elicits inflammatory responses in tumor explantsLaurie Schenkel, Jennifer Molina, Kerren Swinger, Ryan Abo, Danielle Blackwell, Anne Cheung, William Church, Kristy Kuplast-Barr, Alvin Lu, Elena Minissale, Mario Niepel, Melissa Vasbinder, Tim Wigle, Victoria Richon, Heike Keilhack, Kevin Kuntz. Ribon Therapeutics, Cambridge, MA

12:30 PM – 12:35 PM
– Discussion

12:35 PM – 12:45 PM
1039 – Fragment-based drug discovery to identify small molecule allosteric inhibitors of SHP2. Philip J. Day, Valerio Berdini, Juan Castro, Gianni Chessari, Thomas G. Davies, James E. H. Day, Satoshi Fukaya, Chris Hamlett, Keisha Hearn, Steve Hiscock, Rhian Holvey, Satoru Ito, Yasuo Kodama, Kenichi Matsuo, Yoko Nakatsuru, Nick Palmer, Amanda Price, Tadashi Shimamura, Jeffrey D. St. Denis, Nicola G. Wallis, Glyn Williams, Christopher N. Johnson. Astex Pharmaceuticals, Inc., Cambridge, United Kingdom, Taiho Pharmaceutical Co., Ltd, Tsukuba, Japan

Abstract: The ubiquitously expressed protein tyrosine phosphatase SHP2 is required for signalling downstream of receptor tyrosine kinases (RTKs) and plays a role in regulating many cellular processes. Recent advances have shown that genetic knockdown and pharmacological inhibition of SHP2 suppresses RAS/MAPK signalling and inhibits proliferation of RTK-driven cancer cell lines. SHP2 is now understood to act upstream of RAS and plays a role in KRAS-driven cancers, an area of research which is rapidly growing. Considering that RTK deregulation often leads to a wide range of cancers and the newly appreciated role of SHP2 in KRAS-driven cancers, SHP2 inhibitors are therefore a promising therapeutic approach.
SHP2 contains two N-terminal tandem SH2 domains (N-SH2, C-SH2), a catalytic phosphatase domain and a C-terminal tail. SHP2 switches between “open” active and “closed” inactive forms due to autoinhibitory interactions between the N-SH2 domain and the phosphatase domain. Historically, phosphatases were deemed undruggable as there had been no advancements with active site inhibitors. We hypothesised that fragment screening would be highly applicable and amenable to this target to enable alternative means of inhibition through identification of allosteric binding sites. Here we describe the first reported fragment screen against SHP2.
Using our fragment-based PyramidTM approach, screening was carried out on two constructs of SHP2; a closed autoinhibited C-terminal truncated form (phosphatase and both SH2 domains), as well as the phosphatase-only domain. A combination of screening methods such as X-ray crystallography and NMR were employed to identify fragment hits at multiple sites on SHP2, including the tunnel-like allosteric site reported by Chen et al, 2016. Initial fragment hits had affinities for SHP2 in the range of 1mM as measured by ITC. Binding of these hits was improved using structure-guided design to generate compounds which inhibit SHP2 phosphatase activity and are promising starting points for further optimization.

  • anti estrogen receptor therapy: ER degraders is one class
  • AZ9833 enhances degradation of ER alpha
  • worked in preclinical mouse model (however very specific)
  • PK parameters were good for orally available in rodents;  also in vitro and in vivo correlation correlated in rats but not in dogs so they were not sure if good to go in humans
  • they were below Km in rats but already at saturated in dogs, dogs were high clearance
  • predicted human bioavailability at 40%

 

12:45 PM – 12:50 PM
– Discussion

12:50 PM – 1:00 PM
1042 – Preclinical pharmacokinetic and metabolic characterization of the next generation oral SERD AZD9833Eric T. Gangl, Roshini Markandu, Pradeep Sharma, Andy Sykes, Petar Pop-Damkov, Pablo Morentin Gutierrez, James S. Scott, Dermot F. McGinnity, Adrian J. Fretland, Teresa Klinowska. AstraZeneca, Waltham, MA

1:00 PM – 1:05 PM
– Discussion

1:05 PM – 1:15 PM
– Closing RemarksChristopher G. Nasveschuk. MA

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Advancing Drug Development – 12/12/2019, 8:30AM – 8:30PM at The University of Massachusetts Club, One Beacon Street, Boston, MA

Posted in Drug Delivery Platform Technology, Drug Development Process, Drug Discovery Chemistry, Pharmaceutical Discovery, Pharmaceutical Drug Discovery, Pharmaceutical R&D Informatics, Pharmaceutical R&D Investment, Pharmacogenomics, Rapid automation of plasma protein pools on November 4, 2019| Leave a Comment »

Advancing Drug Development – 12/12/2019, 8:30AM – 8:30PM at The University of Massachusetts Club, One Beacon Street, Boston, MA

 

Reporter: Aviva Lev-Ari, PhD, RN

4th Advancing Drug Development Forum – Making the Impossible Possible – Harnessing Small Molecule Drug Development scheduled to take place December 12th, 2019 at The University of Massachusetts Club, in Boston, Massachusetts from 8:30 AM – 8:30 PM.

http://advdrug.com/agenda/

 

Scientists are more than just chipping away and kicking down the barricades to develop complex small molecule products better and faster.  Successful companies are spending quality time finding novel and clever approaches and powerful technologies to better support their knowledgeable teams.  Often it takes establishing strong partnerships with 1 or more specialized service providers, cleverly combining resources – always striving to raise the bar in order to make life threatening diseases more of a chronic and tolerable disease or eradicated completely.

Hear from key opinion leaders in pharma, biotech, the investment community and innovative service providers on how they are meeting the challenges. Keep in mind, it takes being open-minded, flexible and willing sometimes to redesigning a new formulation that better enhances bioavailability, optimizes drug-delivery profiles, reduces dosing frequency, or improves the patient experience to have the potential to deliver quicker returns on investments than developing a completely new drug.

PROGRAM AGENDA Thursday, December 12, 2019
8:30 AM Registration and Networking Continental Breakfast
9:00 AM Welcome Address and Opening Remarks
Kevin Bittorf, Ph.D., & Shelly Amster
9:15 AM Opening VC Keynote
9:45 AM Bridging the Gap between Experimentation and Implementation
Panel Discussion
10:15 AM Refreshment Break
10:45 AM Cross-Talk Between Clin-Ops and Tech-Ops
Panel Discussion
11:15 AM The Cost of Speed and Value in Drug Development
Panel Discussion
12:00 PM Networking Luncheon
1:00 PM Advances in the Delivery of Therapeutics to the Brain
Academic Keynote
Mansoor M. Amiji, Ph.D., University Distinguished Professor, Professor of Pharmaceutical Sciences & Professor of Chemical Engineering, Northeastern University
1:30 PM Advancing Drug Delivery and Controlled Release
Panel Discussion
2:00 PM Drowning in DATA
2:30 PM Disruptive AI Technologies Improving Drug Development
3:00 PM Refreshment Break
3:30 PM Small Specialty VS Full Service – What Makes Sense for US?
Panel Discussion
4:00 PM Fireside Chat
Michael Bonney, Executive Chair, Kaleido Biosciences
Heinrich Schlieker, Ph.D., SVP Technical Operations, Sage Therapeutics
5:00 PM – 8:00 PM Networking Social
Direct electronic communication with Shelly Amster

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Drug Repurposing Hub Library @broadinstitute @MIT @Harvard

Posted in Drug Development Process, Drug Discovery Chemistry, drug repurposing, Pharmaceutical Drug Discovery on February 14, 2019| Leave a Comment »

Drug Repurposing Hub Library @broadinstitute @MIT @Harvard

Reporter: Aviva Lev-Ari, PhD, RN and Irina Robu, PhD

CLAIMER: most valuable information for Drug Repurposing is found in the following LPBI Group three Intellectual Property Asset Classes

Our intellectual property “IP” consists of three classes of assets as described in detail within live links in the below, listed article.

  • First, the Journal, an ongoing journal of curated, current biomedical research;
  • Second, the books, a collection of 16 volumes of e-books available via Amazon in five specialties of Medicine: Cardiovascular, Genomics, Cancer, Immunology and Precision Medicine; and
  • Third, real-time curation of biotech and medical conferences yielding an e-Proceedings at the end of the conference in One-click operation.

These three IP asset classes are described in details with live links in

eScientific Publishing a Case in Point: Evolution of Platform Architecture Methodologies and of Intellectual Property Development (Content Creation by Curation) Business Model

https://pharmaceuticalintelligence.com/2019/02/04/escientific-publishing-a-case-in-point-evolution-of-platform-architecture-methodologies-and-of-intellectual-property-development-content-creation-by-curation-business-model/

 

The Drug Repurposing Hub: A next-generation drug library and information resource

M Corsello, Steven & A Bittker, Joshua & Liu, Zihan & Gould, Joshua & McCarren, Patrick & E Hirschman, Jodi & E Johnston, Stephen & Vrcic, Anita & Wong, Bang & Khan, Mariya & Asiedu, Jacob & Narayan, Rajiv & C Mader, Christopher & Subramanian, Aravind & R Golub, Todd. (2017). The Drug Repurposing Hub: A next-generation drug library and information resource. Nature Medicine. 23. 405-408. 10.1038/nm.4306.

… Published on January 3, 2018 as DOI: 10.1124/mol.117. Downloaded from additional source, we used data from the Broad repurposing hub ( Corsello et al, 2017), which employed high throughput screening to characterize drug-target interactions of approved drugs, natural products and nutraceuticals along with other entities. Our analysis yielded a list of currently ‘druggable’ GPCRs and the drugs that target them. …
… Using a range of ~500 (conservative estimate) to ~700 GPCR-targeted drugs, we estimate that between ~25% and ~36% of approved drugs target GPCRs, with the upper figure the more likely. As additional studies such as the Broad repurposing initiative ( Corsello et al, 2017) characterize GPCR-drug interactions in more detail, we anticipate a growth in this number, as secondary interactions between GPCRs and drugs are defined ( Allen and Roth, 2011). IUPHAR lists more druggable GPCRs than CHEMBL or DRUGBANK but has the smallest number of GPCR-related and overall approved drugs ( Figure 3C shows the number of GPCR-targeted drugs based on target-ligand interactions annotated by either IUPHAR or CHEMBL; of the 476 such drugs listed in one or both sources, only a portion are common to both (50%). …

 

Drug Repurposing Hub Library @broadinstitute  @MIT @Harvard

To date there has not been a systematic effort to identify such opportunities, limited in part by the lack of a comprehensive library of clinical compounds suitable for testing. To address this challenge, we hand-curated a collection of 4,707 compounds, experimentally confirmed their identity, and annotated them with literature-reported targets. The collection includes 3,422 drugs that are marketed around the world or that have been tested in human clinical trials. Compounds were obtained from more than 50 chemical vendors and the purity of each sample was established. We have thus established a blueprint for others to easily assemble such a repurposing library, and we have created an online Drug Repurposing Hub (www.broadinstitute.org/repurposing) containing detailed annotation for each of the compounds.

SOURCE

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5568558/

. Author manuscript; available in PMC 2017 Aug 23.
Published in final edited form as:
PMCID: PMC5568558
NIHMSID: NIHMS893143
PMID: 28388612

The Drug Repurposing Hub: a next-generation drug library and information resource

Steven M. Corsello,1,2,3 Joshua A. Bittker,1 Zihan Liu,1 Joshua Gould,1Patrick McCarren,1 Jodi E. Hirschman,1 Stephen E. Johnston,1 Anita Vrcic,1Bang Wong,1 Mariya Khan,1 Jacob Asiedu,1 Rajiv Narayan,1Christopher C. Mader,1 Aravind Subramanian,1 and Todd R. Golub1,3,4,5,*
SOURCE
Other Resources

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Record Innovations in Drug Discovery by Koch Institute @MIT Members and Affiliates

Posted in BioTechnology - Venture Creation, BioTechnology - Venture Creation, Venture Capital, CANCER BIOLOGY & Innovations in Cancer Therapy, DNA repair, Drug Delivery Platform Technology, Drug Development Process, Drug Discovery Chemistry, MHC Repertoires for Antigen Prediction, Personalized and Precision Medicine & Genomic Research, Pharmaceutical Discovery on February 6, 2019| Leave a Comment »

Record Innovations in Drug Discovery by Koch Institute @MIT Members and Affiliates

Reporter: Aviva Lev-Ari, PhD, RN

 

 

In Good Company

Trovagene announced a new patent for the use of the drug onvansertib in combination with other anti-androgen drugs for the treatment of prostate cancer. Last fall, Trovagene secured exclusive rights to develop combination therapies and clinical biomarkers for prostate cancer based in part on Bridge Project-funded research. Read more.

Lyndra Therapeutics, co-founded by KI member Bob Langer, raised $55 million in its Series B round, with new investors including the Bill and Melinda Gates Foundation and Gilead Sciences. Phase 2 trials for its ultra long-acting drug delivery capsule are expected to begin next year. Read more.

Dragonfly Therapeutics, co-founded by KI director Tyler Jacks, has committed $10 million to launch the first clinical studies of its TriNKETs (Tri-specific, NK cell Engager Therapies) platform for both solid tumor and hematological cancers. Read more.

Following its record-breaking IPO, Moderna Therapeutics (co-founded by KI member Bob Langer) published preclinical data in Science Translational Medicine demonstrating the promise of its mRNA-2752 program in several cancers. Read more.

Dewpoint Therapeutics launched with a $60 million Series A, aims to translate recent insights into biomolecular condensates from the laboratory of co-founder and KI member Rick Young to drug discovery. Read more.

KI member Bob Langer and collaborator Omid Farokhzad co-founded Seer— combining nanotechnology, protein chemistry, and machine learning—to develop liquid biopsy tests for the early detection of cancer and other diseases. Read more.

Epizyme, co-founded by KI member Bob Horvitz, is submitting a New Drug Application to gain accelerated approval of tazemetostat for patients with relapsed or refractory follicular lymphoma. Read more.

Ribon Therapeutics, founded by former KI member Paul Chang, launched with $65 million in a Series B funding round with Victoria Richon, a veteran of Sanofi and Epizyme, at the helm. Ribon focuses on developing PARP7 inhibitors for cancer treatment. Read more.

SOURCE

From: MIT Koch Institute for Integrative Cancer Research <cancersolutions=mit.edu@cmail19.com> on behalf of MIT Koch Institute for Integrative Cancer Research <cancersolutions@mit.edu>

Reply-To: <ki-communications@mit.edu>

Date: Wednesday, February 6, 2019 at 3:15 PM

To: Aviva Lev-Ari <AvivaLev-Ari@alum.berkeley.edu>

Subject: Lung Microbiome Corrupted in Cancer; Angelika Amon wins 2019 Vilcek Award; Lunch Lines of Inquiry

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