On December 14, 2021 Cellworks Group, Inc., a world leader in Personalized Medicine in the key therapeutic areas of Oncology and Immunology, reported results from a clinical study using the Cellworks Biosimulation Platform and Computational Omics Biology Model (CBM) to predict therapy response for individual Acute Myeloid Leukemia (AML) patients were featured in a poster presentation at the 63rd American Society of Hematology (ASH) (Free ASH Whitepaper) Annual Meeting and Exposition held December 11-14, 2021 in Atlanta, Georgia (Press release, Cellworks, DEC 14, 2021, View Source [SID1234597129]). The complete results from this study are available online in the ASH (Free ASH Whitepaper) Meeting Library as Abstract 1299.

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In the study, the Cellworks Biosimulation Platform and CBM was used to assess cytarabine (ARA-C) and anthracycline response and novel biomarker response criteria for the addition of etoposide (VP16) in AML. The study found that Cellworks biosimulation identifies novel biomarkers that predict therapy response in AML patients, which offers the opportunity to tailor FDA-approved chemotherapy regimens to each patient to improve disease control and minimize toxicity. In addition, biosimulation is emerging as an essential tool to improve the success rate of clinical trials and speed the development of lifesaving medicines for the patients that need them.

"From comprehensive genomic inputs, the Cellworks Biosimulation Platform identifies pathway based polygenic biomarkers that predict the efficacy of novel drug combinations and new drugs for AML patients," said Dr. Michael Castro, MD, Chief Medical Officer at Cellworks. "Cellworks AML biomarker identification and therapy response prediction capabilities should accelerate clinical trials for new therapies and improve trial success rates by predicting if a patient’s genomic profile will respond to specific regimens. Biosimulation has the ability to improve outcomes for patients, avoid drugs that produce only toxicity and extend the reach of precision medicine in the clinic."

The Cellworks Biosimulation Platform simulates how a patient’s personalized genomic disease model will respond to therapies prior to treatment and identifies novel drug combinations for treatment-refractory patients. The platform is powered by the groundbreaking Cellworks Computational Omics Biology Model (CBM), a network of 4,000+ human genes, 30,000+ molecular species and 100+ signaling pathways. By reliably predicting an individual patient’s therapy response prior to receiving the treatment, the Cellworks Platform can guide the selection of the optimal treatment, help patients avoid ineffective therapies and improve patient outcomes.

Clinical Study: ASH (Free ASH Whitepaper) Abstract 1299

Biosimulation using Cellworks Computational Omics Biology Model (CBM)-based assessment of cytarabine (ARA-C) and anthracycline response and novel biomarker response criteria for the addition of etoposide (VP16) in AML.

Background

Genomic heterogeneity in leukemic blasts characterizes AML patients and is associated with variable drug responses. In this study, 539 AML patients were selected based largely on genomic data published in TCGA and PubMed. The Cellworks Biosimulation Platform and Computational Omics Biology Model (CBM) was used to identify novel genomic biomarkers associated with response among AML patients treated with cytarabine (ARA-C) + idarubicin or daunorubicin (anthracycline) with or without etoposide (VP16).

Results

Cellworks biosimulation of ARA-C + anthracycline with and without VP16 identified biomarkers responsible for therapy responses. Additionally, the biosimulation identified novel drug combinations for non-response to these standard combinations. Altogether, 89 of the 539 patients (16.5%) could have been managed with a potentially superior treatment approach based on the biosimulation by either adding or omitting VP16 or being treated with an alternative therapy.

Conclusion

This study highlights patients for whom triplet therapy promises potential superior benefit, others who would benefit equally from doublet therapy without VP16 and others unlikely to respond to standard or triplet therapy for whom an alternative personalized approach might offer better outcomes. In AML, Cellworks biosimulation offers the possibility to tailor the chemotherapy regimen to each patient to improve disease control and minimize toxicity.

On December 14, 2021 AnHeart Therapeutics ("AnHeart"), a clinical-stage global biopharmaceutical group company committed to developing novel precision oncology therapies, reported the completion of a $61 million oversubscribed Series B financing round led by new investor Octagon Capital, with participation from Innovent Biologics, Cenova, Laurion Capital, and Sage Partners (Press release, AnHeart Therapeutics, DEC 14, 2021, View Source [SID1234597125]). The Company has raised a total of $100 million in gross proceeds from private financings since its founding in December 2018.

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The proceeds from the Series B financing will be used to advance the clinical development of AnHeart’s lead asset, taletrectinib, a next-generation ROS1 inhibitor currently in Phase 2 trials in non-small cell lung cancer (NSCLC), and support the continued expansion of its pipeline of precision next-generation oncology therapeutics.

ROS1 oncogenic fusions are observed in approximately 1-2% of or about 20,000 NSCLC patients each year worldwide. ROS1 fusions are also observed in several other cancers such as cholangiocarcinoma, glioblastoma, ovarian, gastric, and colorectal cancers. NTRK fusions are oncogenic driver across multiple advanced solid tumors and observed in more than 90% in very rare cancers such as secretory breast carcinoma, mammary analogue secretory carcinoma of salivary gland and infantile fibrosarcoma, 12.1~14.5% of papillary thyroid cancer and 10.3% of non-brainstem high grade glioma. Incidence of NTRK fusions is below 5% in more common cancers such as lung, breast, melanoma, and colon cancer.

Taletrectinib is a potent, novel, highly selective, next-generation ROS1/NTRK inhibitor for solid tumors with ROS1 fusion or NTRK fusion mutations. It can overcome crizotinib resistance and cross the blood-brain barrier. There is currently no FDA approved drug targeting crizotinib resistance mutations. Taletrectinib is currently in China TRUST trial (Taletrectinib ROS1 LUng STudy, NCT04395677), global TRUST II trial (NCT04919811) and the basket trial in NTRK fusion positive solid tumors (NCT04617054). Impressive interim data of the TRUST Phase 2 trial for NSCLC have been published at ASCO (Free ASCO Whitepaper) and CSCO earlier this year.

"AnHeart is delighted to partner with this group of top-tier, leading healthcare investors to advance development of our pipeline of precision oncology therapeutics. We have made tremendous progress since we founded AnHeart in 2018," Junyuan (Jerry) Wang, Ph.D., Co-Founder and Chief Executive Officer of AnHeart Therapeutics. "This financing reflects strong support for our platform, people, and comprehensive development strategy."

"This strong investment group, comprised of both healthcare specialist funds and a leading biopharma company allows us to accelerate development of our unique pipeline of targeted therapies," said Lihua Zheng, J.D., Ph.D., Co-Founder and Chief Business Officer of AnHeart Therapeutics. "The funding will also allow us to continue expanding our team of world-class scientists and researchers focused on bringing game-changing cancer therapeutics to improve patients’ lives."

"We were attracted to AnHeart by the excellent science, experienced management team and broad pipeline of targeted small molecule therapeutics," said Dr. Ting Jia, "TJ", Ph.D., Founder, Octagon Capital, a New York-based healthcare specialist fund active in both private and public markets. "AnHeart’s lead asset taletrectinib is a promising potential new therapeutic in ROS1 fusion-positive lung cancer patients, with impressive preliminary Phase 2 clinical data reported at ASCO (Free ASCO Whitepaper) and CSCO this year. In addition, we see a tremendous opportunity for AnHeart’s pipeline to produce novel, targeted therapies to address significant unmet medical needs across a broad range of difficult-to-treat cancers."

On December 14, 2021 Cellworks Group, Inc., a world leader in Personalized Medicine in the key therapeutic areas of Oncology and Immunology, reported results from the myCare-023 clinical trial, which found that the Cellworks Biosimulation Platform with its Therapy Response Index (TRI) reliably predicts complete response (CR) and overall survival (OS) for individual Acute Myeloid Leukemia (AML) patients beyond physician prescribed treatment (Press release, Cellworks, DEC 14, 2021, View Source [SID1234597124]). The myCare-023 study also showed that the Cellworks platform can provide personalized, molecular-based alternate treatment options for AML patients who are predicted to be non-responders to standard care therapies.

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"Except for a few targeted therapies, genomic assessment has offered little guidance on treatment for AML patients," said Dr. Guido Marcucci, MD, Chair and Professor, Department of Hematologic Malignancies Translational Science; Director, Gehr Family Center for Leukemia Research, and Chief of Leukemia Division within the Department of Hematology & Hematopoietic Cell Transplantation, City of Hope; and Principal Investigator for the myCare-023 clinical trial. "This study shows that the Cellworks Biosimulation Platform has the potential to improve treatment guidance by utilizing a comprehensive molecular genomic network to model each patient’s unique cancer and predict how they will respond to specific treatments. Through this personalized therapy biosimulation approach, we can individualize treatment selection and improve patient outcomes."

The results from the myCare-023 clinical trial were featured as an oral presentation given by Dr. Scott Howard, MD, MSc, at the 63rd American Society of Hematology (ASH) (Free ASH Whitepaper) Annual Meeting and Exposition on December 13, 2021 in Atlanta, Georgia and available online in the ASH (Free ASH Whitepaper) Meeting Library as Abstract 689.

"Complete remission and cure rates for AML have significant room for improvement," said Dr. Scott Howard, MD, MSc, University of Tennessee Health Science Center. "Comprehensive molecular profiling shows us that AML is a complex and heterogeneous disease network which impacts the efficacy of individual chemotherapeutics differently in individual patients. By using the Cellworks personalized therapy biosimulation platform to predict the impact of an individual patient’s aberrations and copy number alternations on therapy response, we can address the heterogeneous nature of AML and improve complete remission and cure rates."

The Cellworks Biosimulation Platform simulates how a patient’s personalized genomic disease model will respond to therapies prior to treatment and identifies novel drug combinations for treatment-refractory patients. The platform is powered by the groundbreaking Cellworks Computational Omics Biology Model (CBM), a network of 4,000+ human genes, 30,000+ molecular species and 100+ signaling pathways. As part of the biosimulation process, personalized disease models are created for each patient using their cytogenetic and molecular data as input to the Cellworks CBM. The Cellworks platform analyzes the impact of specific therapies on the patient’s personalized disease model and generates a Singula biosimulation report with Therapy Response Index (TRI) Scores that predict the efficacy of specific chemotherapies.

"The use of genomics to guide therapy for AML patients has generally been restricted to a single-gene approach, which rarely has sufficient predictive power to be clinically useful," said Dr. Guido Marcucci, MD. "However, comprehensive DNA sequencing used with Cellworks personalized therapy biosimulation can guide optimal treatment selection for individual patients, help patients avoid ineffective therapies and improve patient outcomes."

Clinical Study: myCare-023

ASH Abstract 689: Therapy biosimulation using the Cellworks Computational Omics Biology Model (CBM) is predictive of individual AML patient probability of clinical response and overall survival.

Methods

Cytogenetic and molecular data obtained from clinical trials including AMLSG 07-04, Beat AML, TCGA and PubMed publications was used to create a personalized in silico models of each patient’s AML. The impact of specific AML therapies on each patient’s disease model was biosimulated to determine a treatment efficacy score by estimating the effect of chemotherapy on the cell growth score, a composite of cell proliferation, viability, apoptosis, metastasis, DNA damage and other cancer hallmarks. The mechanism of action of each therapy was mapped to each patient’s genome and biological consequences determined response.

Results

In this study, specific leukemia therapies generated a variable likelihood of benefit for individual patients. The Cellworks TRI score, scaled from 0 to 100, predicted complete response with a likelihood ratio χ12 = 52.54, p < 0.0001. The Cellworks Biosimulation Platform was able to predict treatment benefit or failure better than physician prescribed treatment alone (likelihood ratio χ12 = 14.86, p < 0.0001). The use of therapy biosimulation to select therapy is estimated to increase odds of complete response by 19% per every 25 units of the TRI score.

TRI scores were also a significant predictor of overall survival (likelihood ratio χ12 = 80.41, p < 0.0001) and provides predictive information above and beyond physician prescribed treatment alone (likelihood ratio χ12 = 58.70, p < 0.0001). Inclusion of the Cellworks biosimulation is estimated to reduce the hazard ratio for death above and beyond physician prescribed treatment by 16% per every 25 units of the TRI score.

In addition, predictiveness curves suggest that approximately 25% of de novo AML patients had low probability of complete response resulting in lower overall survival and could benefit substantially from inclusion of therapies and combinations identified by Cellworks biosimulation into frontline management.

Conclusions

This study found that Cellworks TRI predicts complete response and overall survival beyond physician prescribed treatment alone and the Cellworks platform provides individualized, molecular-based alternate treatment options for patients predicted to be non-responders to standard care therapies.

On December 14, 2021 Cellworks Group, Inc., a world leader in Personalized Medicine in the key therapeutic areas of Oncology and Immunology, reported clinical study results using the Cellworks Biosimulation Platform and Computational Omics Biology Model (CBM) to predict therapy response for individual Mantle Cell Lymphoma (MCL) patients were featured in a poster presentation at the 63rd American Society of Hematology (ASH) (Free ASH Whitepaper) Annual Meeting and Exposition held December 11-14, 2021 in Atlanta, Georgia (Press release, Cellworks, DEC 14, 2021, View Source [SID1234597121]). The complete results from this study are available online in the ASH (Free ASH Whitepaper) Meeting Library as Abstract 3550.

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The study used the Cellworks Biosimulation Platform and CBM to predict novel biomarkers for Hyper-CVAD treatment response and combination of Rituximab and Cladribine (RC) in CVAD resistant cases of MCL. The study found that the Cellworks Platform can be useful to identify treatment alternatives for patients with low likelihood of response to standard therapy or who may be ineligible for CVAD because of co-morbidities.

"The use of reliable and predictive biomarkers to guide the optimal treatment strategy for MCL patients with diverse genomic profiles remains a critical unmet need in the clinic and would be valuable for clinical trial patient selection," said Dr. Michael Castro, MD, Chief Medical Officer at Cellworks. "Genomics-guided therapy for MCL patients is generally restricted to a single-gene approach, which rarely has sufficient predictive power to be clinically useful for relapsed patients. However, the use of comprehensive DNA sequencing and Cellworks personalized biosimulation can predict therapy response for individual patients with diverse genomic profiles in advance of treatment. Utilizing personalized therapy biosimulation prior to enrolling patients in clinical trials can positively affect the success of studies and accelerate the approval of new therapies, which ultimately improves patient outcomes."

The Cellworks Biosimulation Platform simulates how a patient’s personalized genomic disease model will respond to therapies prior to treatment and identifies novel drug combinations for treatment-refractory patients. The platform is powered by the groundbreaking Cellworks Computational Omics Biology Model (CBM), a network of 4,000+ human genes, 30,000+ molecular species and 100+ signaling pathways. By reliably predicting an individual patient’s therapy response prior to receiving the treatment, the Cellworks Platform can guide the selection of the optimal treatment, help patients avoid ineffective therapies and improve patient outcomes.

Clinical Study: ASH (Free ASH Whitepaper) Abstract 3550

Biosimulation using the Cellworks Computational Omics Biology Model (CBM) predicted novel biomarkers for Hyper-CVAD treatment response and combination of Rituximab and Cladribine (RC) in CVAD resistant cases of MCL.

Background

Hyper-CVAD (CVAD) with or without Rituximab constitutes first line therapy for treatment of MCL, yet the use of this combination is associated with high toxicity and only modest efficacy. But impressive clinical efficacy has been reported in relapsed MCL patients treated with Rituximab and Cladribine (RC). Predicting response based on cancer genomic heterogeneity creates an opportunity to personalize treatment and avoid toxic therapy which has little chance of response.

Results

Ninety-four newly-diagnosed MCL patients were selected for the study based largely on genomic data published in PubMed and TCGA. Among the 94 MCL patients treated with CVAD, the Cellworks Biosimulation Platform identified novel biomarkers to predict treatment response or failure. The biosimulation also identified unique drug combinations for patients that were non-responders to both treatments. In considering both regimens, 27 patients were predicted as responders to both CVAD and RC, 14 to RC but not to CVAD, 30 to CVAD but not RC and 23 as not responders to both regimes. For the latter group, biosimulation predicted that a venetoclax-based combination would be effective in many cases due to the high incidence of TP53 GOF mutation within this subgroup.

Conclusion

By using novel biomarkers derived from comprehensive mutational and copy number analysis, the Cellworks Biosimulation Platform identified pathway-based, polygenic biomarkers that can determine optimal therapy combinations for MCL patients. The Cellworks Platform can be useful to identify treatment alternatives for patients with low likelihood of response to standard therapy or who may be ineligible for CVAD because of co-morbidities.

On December 14, 2021 Cellworks Group, Inc., a world leader in Personalized Medicine in the key therapeutic areas of Oncology and Immunology, reported the results from two clinical studies using the Cellworks Biosimulation Platform and Computational Omics Biology Model (CBM) to predict therapy response for individual MDS patients were featured in two poster presentations at the 63rd American Society of Hematology (ASH) (Free ASH Whitepaper) Annual Meeting and Exposition held December 11-14, 2021 in Atlanta, Georgia (Press release, Cellworks, DEC 14, 2021, View Source [SID1234597117]). The complete results from these clinical studies are available online in the ASH (Free ASH Whitepaper) Meeting Library as Abstract 2615 and Abstract 3690.

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In the ASH (Free ASH Whitepaper) Abstract 2615 study, the Cellworks Biosimulation Platform and CBM identified genomic and molecular markers for decitabine (DAC) plus valproic-acid (VPA) treatment response in patients with Myelodysplastic Syndromes (MDS). In the ASH (Free ASH Whitepaper) Abstract 3690 study, the Cellworks Biosimulation Platform and CBM identified immune modulation as a key pathway for predicting azacitidine (AZA) response in MDS.

"There is a need for a predictive clinical approach that can stratify MDS patients according to their chance of a favorable outcome from current therapies, while also identifying and predicting their responses to new and emerging treatment options," said Dr. Michael Castro, MD, Chief Medical Officer at Cellworks. "Ideally, patients predicted to be non-responders could be offered to participate in a clinical trial for a new therapy or combination treatment where they were predicted to have a higher likelihood of response based on their genetic biomarkers. By using Cellworks MDS biomarker identifications and therapy response predictions in advance of participation in a clinical trial, pharmaceutical companies can increase the success rate of trials and accelerate the approval timeframe for new treatments."

The Cellworks Biosimulation Platform simulates how a patient’s personalized genomic disease model will respond to therapies prior to treatment and identifies novel drug combinations for treatment-refractory patients. The platform is powered by the groundbreaking Cellworks Computational Omics Biology Model (CBM), a network of 4,000+ human genes, 30,000+ molecular species and 100+ signaling pathways. By reliably predicting an individual patient’s therapy response prior to receiving the treatment, the Cellworks Platform can guide selection of the optimal treatment, help patients avoid ineffective therapies and improve patient outcomes.

Clinical Study: ASH (Free ASH Whitepaper) Abstract 2615

Biosimulation using the Cellworks Computational Omics Biology Model (CBM) identifies genomic and molecular markers for decitabine (DAC) plus valproic-acid (VPA) treatment response in patients with Myelodysplastic Syndromes (MDS).

Background

DNA methyltransferase inhibition (DNMTi) with hypomethylating agents (HMA), azacitidine (AZA) or decitabine (DAC), remains the mainstay of therapy for most high-risk MDS patients. However, only 40-50% of MDS patients achieve clinical improvement with DNMTi. This study explored the molecular basis of observed clinical response in a group of patients treated with DAC and valproic-acid (VPA). Biosimulations were conducted on each patient-specific disease model to measure the effect of DAC + VPA according to a cell growth score.

Results

In the biosimulation, VPA is a relatively weak HDAC inhibitor, but it also inhibits GSK3B and in turn increases beta-catenin (CTNNB1) levels. Additionally, monosomy 7 associated with loss of CAV1, HIPK2 and TRRAP also caused high CTNNB1, thereby further contributing to drug resistance. Biosimulation correctly identified that 7 of 8 patients with these genomic findings were clinical non-responders to VPA, indicating that CTNNB1 status is likely to predict treatment failure from the VPA + HMA combination in this disease. By contrast, high levels of c-MYC predict response to VPA + HMA combination.

Conclusions

Cellworks Biosimulation Platform found that signaling pathway consequences related to CTNNB1 and c-MYC modulation predict response to DAC + VPA. Although HMA plus HDAC inhibition can be generally beneficial for MDS, variable mechanisms of action among various HDAC inhibitors and unique patient disease characteristics should be considered for optimal treatment selection. Also, CTNNB1 emerged from the Cellworks biosimulations as a therapeutically relevant target in MDS that determines whether VPA synergizes or antagonizes the effect of other agents in this challenging subtype of MDS.

Clinical Study: ASH (Free ASH Whitepaper) Abstract 3690

Biosimulation using the Cellworks Computational Omics Biology Model (CBM) identifies immune modulation as a key pathway for predicting azacitidine (AZA) response in MDS.

Background

Only 40-50% of MDS patients achieve clinical improvement with DNMTi, the mainstay of therapy for the majority of high-risk MDS patients. Recently, a discovery of immune modulation by HMA has emerged. Although the PD-L1/PD1 blockade plus HMA has been recognized as a beneficial combination, there are no established markers to guide decision-making. This study analyzed the utility of immunomic profiling of chromosome 9 copy number status as a significant mechanism of immune evasion and HMA resistance.

Results

Although AZA treatment increased tumor associated antigens and interferon signaling, it also increased PD-L1 expression to inactivate cytotoxic CD8(+) T cells. Copy number alternations of the chromosome 9p region were found to significantly drive PD-L1 expression with multiple genes such as CD274, IFNA1, JAK2, PDCD1LG and KDM4C playing a role in PD-L1 regulation further increasing immune suppression.

Conclusion

Based on the results from the Cellworks Biosimulation Platform and Computational Biology Model (CBM), copy number variants of chromosome 9p and 16 can be used as biomarkers for selecting patients that may achieve high clinical benefit from addition of immune checkpoint inhibitors to HMA regimen.