Cell Works Group, Inc.

Peer-Reviewed Research Indicates Whole Genome Biosimulation Holds Promise for Personalized Therapy Selection in Clinical Settings SOUTH SAN FRANCISCO, Calif.--(BUSINESS WIRE)-- Cellworks Group Inc., a leader in Personalized Therapy Decision Support and Precision Drug Development, today announced the results from a real-world study of gastroesophageal cancer which found that Therapy Response Index (TRI) scores generated using the Cellworks Biosimulation Platform predicted overall survival (OS) above and beyond standard clinical factors, including patient age, sex, and tumor-node-metastasis (TNM) staging. The study also showed a significant association between a patient’s TRI score and disease-free survival (DFS) and tumor regression grade (TRG). The peer-reviewed paper, ‘Integration of genomic aberrations to predict clinical outcomes for patients with gastroesophageal adenocarcinoma receiving neoadjuvant chemotherapy,’ is available at ESMO Gastrointestinal Oncology. Despite progress in gastroesophageal cancer therapy, only a small proportion of patients attain long-term survival. Previous precision-based strategies have been constrained by focusing on single biomarker–drug associations. This oversimplified approach to the disease has resulted in a wide spectrum of patient outcomes, with long-term survival rates spanning from 25% to 75% using multi-modality therapy — a combination of chemotherapy, radiation, surgical resection, and adjuvant nivolumab, which has become the standard of care. “The focus for guiding treatment decisions for gastroesophageal patients has centered on specific biomarkers such as HER2, MSI, PD-L1 and CLD18.2,” said Dr. Elizabeth Smyth, Oxford University Hospitals NHS Foundation Trust; and Co-Principal Investigator of the study. “However, further refinement of treatment selection using computational biomarkers might be possible. This study highlights the unique value that Cellworks computational biosimulation can bring to the treatment decision process by utilizing a patient's comprehensive genomic pro biosimulating all possible therapy combinations. This approach could offer a promising avenue for recommending a treatment strategy at an individual level, thereby improving patient outcomes." "The size and complexity of comprehensive genomic panels pose a formidable challenge, making it difficult for oncologists to translate the intricate biology into actionable clinical decisions,” said Dr. Rebecca Fitzgerald, MD, Professor of Cancer Prevention at the University of Cambridge; Director of the Early Cancer Institute; and Co-Principal Investigator of the study. “This study demonstrates that utilizing whole genome sequencing of a patient’s gastroesophageal cancer along with Cellworks personalized biosimulation approach has the potential to highlight when alternative treatment strategies such as fluoropyrimidines, taxanes, anthracyclines or platinum compounds may yield superior outcomes for a specific patient." "The transition from small panel NGS to whole exome and whole genome sequencing brings new insights about each cancer’s complex proteogenomic network,” said Dr. Michael Castro M.D., Oncologist at Beverly Hills Cancer Center; and Chief Medical Officer at Cellworks, Group Inc. “These insights reveal the basis for drug sensitivity and resistance that allows oncologists to select the optimal combination therapy for individual patients and creates the possibility of targeting the sources of therapeutic resistance. The view that genomic information is ‘unactionable’ is transformed by artificial intelligence (AI)-level molecular diagnosis provided by Cellworks’ biosimulation. Most genomic information that can be measured is highly relevant to tumor biology and treatment response but is beyond the grasp of busy clinicians. With Cellworks biosimulation, the oncogene-only approach to precision medicine is already obsolete.” Clinical Study Methods The performance of Cellworks in silico biosimulation and Therapy Response Index (TRI) scores were studied in patients with gastroesophageal adenocarcinoma (OGA) with operable cancers from the UK Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) International Cancer Genome Consortium study. A total of 270 patients with OGA were selected who had 50x whole genome sequencing carried out on tissue derived from either biopsy or resection within 12 months of treatment. Patients were treated with chemotherapy drugs or regimes according to UK clinical guidelines. Biosimulation was carried out utilizing the Cellworks computational biology model (CBM), which uses both mechanistic and statistical approaches to integrate a patient’s genomic aberrations, revealing signaling pathway dysregulation and variable drug response. Using patient-specific predictions derived from the CBM, a TRI score was used to predict therapeutic overall survival (OS), disease-free survival (DFS) and tumor regression grade (TRG). Results The results of the study revealed that the association of TRI value with overall survival (OS) for gastroesophageal adenocarcinoma patients was significant (P = 0.0012) above and beyond standard clinical factors including patient age, sex, tumor-node-metastasis (TNM) stage and neoadjuvant therapy. The association between TRI values and disease-free survival (DFS) was also significant (P = 0.0288). In addition, the TRI values optimized for tumor regression grade (TRG) displayed a significant association (P = 0.0011). Conclusions This study concluded that TRI scores for gastroesophageal adenocarcinoma patients predict OS and DFS beyond clinical factors. These results highlight the clinical value of employing Cellworks biosimulation for personalized therapy selection and warrant additional clinical evaluation. Cellworks Platform and Therapy Response Index (TRI) The Cellworks Platform biosimulates the impact of specific drug compounds on an individual patient or class of patients using their genomic profile. Multi-omic data from an individual patient or cohort is used as input to the in silico Cellworks Computational Biology Model (CBM) to generate a personalized or cohort-specific disease model. The CBM is a highly curated mechanistic network of 6,000+ human genes, 30,000 molecular species and 600,000 molecular interactions. This model along with associated drug models are used to biosimulate the impact of specific compounds or combinations of drugs on the patient or cohort and produce therapy response predictions, which are statistically modeled to produce a qualitative Therapy Response Index (TRI) score, scaled from 0 (unfavorable outcome) to 100 (favorable outcome) for a specific therapy. The Cellworks CBM has been tested and applied against various clinical datasets with results provided in over 125 presentations and publications with global collaborators. About Cellworks Group Cellworks Group, Inc. is a leader in Personalized Therapy Decision Support and Precision Drug Development. The Cellworks Platform predicts therapy response for individual patients and patient cohorts using a breakthrough Computational Biology Model (CBM) and biosimulation technology. Backed by Artiman Ventures, Bering Capital, Sequoia Capital, UnitedHealth Group and Agilent Ventures, Cellworks has the world’s strongest trans-disciplinary team of molecular biologists, cellular pathway modelers and software engineers working toward a common goal – attacking serious diseases to improve the lives of patients. The company is based in South San Francisco, California with a research and development facility in Bangalore, India. For more information, visit cellworks.life. All trademarks and registered trademarks in this document are the properties of their respective owners.

SOUTH SAN FRANCISCO, Calif.--( BUSINESS WIRE )-- Cellworks Group Inc. , a leader in Personalized Therapy Biosimulation, today announced the launch of its Precision Drug Development business units aimed at accelerating time-to-market for drug development and reviving previously studied but unapproved pharmaceutical assets through predictive biosimulation. The two new business units will use Cellworks’ biosimulation platform and Computational Biology Model (CBM) to predict responses to pharmaceutical interventions in silico , thereby streamlining the clinical trial process by identifying the right patients more rapidly, which in turn reduces the time and expense of developing successful pharmaceutical agents. “Drug development today is a time-consuming and expensive process - it can take a decade or longer to take a new drug to market and cost hundreds of millions of dollars,” said Brian Battey, COO of Cellworks Group. “But in many instances, the Cellworks Platform has the ability to predict the human clinical response to drug candidates years earlier than traditional development pipelines. By predicting human clinical response much earlier in the drug development cycle, we can help pharmaceutical companies shave years off drug development timelines, expand the diseases explored, reduce the cost of thoroughly investigating pharmaceutical assets and get new therapies to patients faster.” Cellworks Precision Drug Development: Pre-clinical Stage Biomarker Development: Cellworks uses cell line data and retrospective patient data to discover novel biomarkers for investigational agents, which can improve drug success rates by prospectively identifying patients who will respond to an agent. Biomarkers can be associated with response or non-response and range from a single-gene biomarker to multi-gene signature. Companion Molecule Development: The Cellworks Platform may be able to expand the utility of a drug by discovering companion molecules that increase performance when administered in combination with the investigational agent. Cellworks leverages hundreds of models from its Drug Library to iteratively add desired agents to a combination and calculate the efficacy for each combination. All combinations that show efficacy are then filtered for further evaluation. Indication Expansion: The Cellworks Platform can potentially identify additional indications where an investigational drug may be effective by leveraging the Cellworks patient database of 100,000+ omics patient profiles and 1,800 oncology cell-lines to evaluate the efficacy of the agent in other indications. Cellworks biosimulation results may provide guidance for additional indications to target for clinical development. “Ninety percent of drug candidates fail to make it to the marketplace because of failed clinical development strategies,” said Dr. Michael Castro, M.D., Chief Medical Officer at Cellworks Group. “Low efficacy is often not because the drug fails to hit its target, but is more often a consequence of a molecularly naïve approach to a heterogenous and complex disease. The Cellworks platform uses computational biosimulation to model signaling pathways, master regulators, hallmark behaviors of cancer, and drug interactions with each patient’s unique disease network. Biosimulation stratifies treatment options according therapeutic impact and enables precision clinical trials that promises to transform the drug development process with fewer failures. Even a modest doubling of successful drug development from 10 to 20% would reduce the development costs for an agent reaching the marketplace by half.” Cellworks Precision Drug Development: Clinical Stage Clinical Trial Biosimulation: By biosimulating clinical trials, the Cellworks Platform may be able to predict human clinical response to pharmaceutical agents in just weeks, delivering critical insights years ahead of a traditional clinical trial. Patient cohorts are selected from the Cellworks patient database of 100,000+ omics profiles of patients based on guidance from the client. Cellworks creates an in-silico model of the drug or drug combination. The impact of the drug(s) is biosimulated with the cohort. Cellworks biosimulation results may provide guidance on the indications to target for clinical development. Drug Revival and Repurposing: The Cellworks Platform aims to predict why specific drugs cause response, or not, which may be used to determine if shelved assets can be revived through appropriate patient selection or identification of non-obvious indications. Cellworks collaborates with pharma and biotech partners on certain assets to enhance development efforts and accelerate commercialization by applying the Cellworks Platform to assets owned by the partner or through in-licensing assets that the partner prefers to have an external innovation partner take on the clinical development and financial responsibilities. Cellworks Platform and Computational Biology Model (CBM) The Cellworks Platform biosimulates the impact of specific drug compounds on an individual patient or class of patients using their genomic profile. Multi-omic data from a patient or cohort is used as input to the Cellworks Computational Biology Model (CBM) to generate a personalized or cohort-specific disease model. The CBM is a highly curated mechanistic network of 6,000+ human genes, 30,000 molecular species and 600,000 molecular interactions. This model along with associated drug models are used to biosimulate the impact of specific compounds or combinations of drugs on the patient or cohort and produce therapy response predictions. The Cellworks CBM has been tested and applied against various clinical datasets with results provided in over 125 presentations and publications with global collaborators. In studies such as iCare1, a prospective observational trial in AML and MD published in Blood Advances , the Cellworks Platform has shown it can more reliably predict response compared to physician choice alone, identify the drugs in a multidrug regimen that are actually working --- not just adding toxicity, suggesting novel treatment regimens for patients who otherwise might have run out of options, and identify biomarkers associated with response and non-response. New Leadership Cellworks has recently added key members to its executive team to propel the company’s growth and commercialization strategy. Over the past six months, Dave Daly has supported the Cellworks business transformation as its CEO. Daly and Yatin Mundkur of Artiman Ventures, a Cellworks investor serving as Chief Technology Officer and Board Director, together lead the Cellworks Platform development strategy and model validation efforts. Other additions to the Cellworks leadership team include: Dr. Michael Castro as Chief Medical Officer; Brian Battey as Chief Operating Officer; James Wingrove, Ph.D . as Vice President of Clinical Services; and Duane Williams as Vice President Pharma Services. In addition, Philip Sawyer , Managing Partner at Bering Capital, has joined the Cellworks Board as a Director and Dr. Lee Newcomer , former Chief Medical Officer of UnitedHealth Group, is now Cellworks Chairman of the Board. The new members of the Cellworks leadership team join Michele Dundas Macpherson , Cellworks Chief Business Officer, and Drew Watson, Ph.D., Cellworks Chief Biostatistician, as the company prepares for exponential growth in the Personalized Oncology and Precision Pharma markets. “This exceptional team will continue to advance industry-leading decision support for personalized therapy selection, while also leveraging the same technology platform to provide precision pharma services that accelerate drug development to get new therapies to patients faster,” said Yatin Mundkur, Cellworks Chief Technology Officer and Board Director. “Cellworks has a unique opportunity to bridge the gap between sequencing data and decision-making for therapy selection,” said Lee Newcomer, M.D., Cellworks Chairman of the Board. “Next Generation Sequencing (NGS) reports uncover genomic aberrations, but patients with multiple aberrations have hundreds of potential pathway disruptions that cannot be predicted without computational technology. The Cellworks Platform and Computational Biology Model use biosimulation to accurately predict the best clinical outcomes for a specific patient considering their full genomic profile.” “Cellworks has assembled a powerhouse team skilled in diagnostic medicine, therapeutic decision making and drug development,” said Brian Battey, COO of Cellworks Group. “We are well-positioned to enhance clinical markets by addressing the significant unmet needs in both precision pharma and personalized oncology. I am looking forward to advancing Cellworks mission to improve patient outcomes through precision drug development and personalized therapy selection.” About Cellworks Group Cellworks Group, Inc. is a leader in Precision Drug Development and Personalized Therapy Biosimulation. The Cellworks Platform predicts therapy response for individual patients and patient cohorts using a breakthrough Computational Biology Model (CBM) and biosimulation technology. Backed by Artiman Ventures, Bering Capital, Sequoia Capital, UnitedHealth Group and Agilent Ventures, Cellworks has the world’s strongest trans-disciplinary team of molecular biologists, cellular pathway modelers and software technologists working toward a common goal – attacking serious diseases to improve the lives of patients. The company is based in South San Francisco, California with a research and development facility in Bangalore, India. For more information, visit www.cellworks.life . All trademarks and registered trademarks in this document are the properties of their respective owners.

Personalized Therapy Biosimulation Uncovers a Spectrum of Genomic Aberrations that Predict Response to HMA in Myelodysplastic Syndrome Patients SOUTH SAN FRANCISCO, Calif.--(BUSINESS WIRE)-- Cellworks Group Inc., a leader in Precision Drug Development and Personalized Therapy Biosimulation, today announced results from a study that examined how Differentiation Scoring (DS) derived from key myeloid biomarkers in individual Myelodysplastic Syndrome (MDS) patients using the Cellworks Platform and Computational Biology Model (CBM) can predict response to Hypomethylating Agents (HMA). In the study, DS predicted HMA response in MDS patients and showed a strong correlation to the treatment efficacy score (ES). Non-responders had lower DS and survival than patients with high DS. Conclusions from the study suggest that DS-low MDS patients should be considered for novel combination therapy at the time of diagnosis. Results from the study were featured in a poster presentation as Abstract 2171 at the 64th American Society of Hematology (ASH) Annual Meeting and Exposition on December 10, 2022 and have been published online at Blood®. “Given that 50% of MDS patients who are treated with HMA as a single agent will have unsatisfactory outcomes, we need to be able to predict therapy response for individual patients prior to treatment,” said Dr. Guido Marcucci, MD, Chair and Professor, Department of Hematologic Malignancies Translational Science, Director, Gehr; Family Center for Leukemia Research, Professor, Department of Hematology & Hematopoietic Cell Transplantation, City of Hope; and Co-Principal Investigator of the study. “This study demonstrates the power of using Cellworks personalized therapy biosimulation to gain insight into individual patient mutanome, drug resistance pathways and novel biomarkers that determine their drug response and resistance to better inform treatment decisions for MDS patients.” “MDS patients typically have multiple molecular aberrations which impact how they respond to treatment,” said Dr. Scott Howard, MD, MSc, Professor at University of Tennessee Health Science Center and Co-Principal Investigator of the study. “This study showcases the complexity of MDS-related aberrations and provides a metric for identifying beforehand which patients will benefit from HMA as a single agent. By identifying which patients will not respond to HMA, clinicians can consider other options such as a combination therapy or a clinical trial.” “Biosimulation of MDS using differentiation scoring was able to identify patients with minimal benefits from HMA for whom an alternative strategy at the outset of treatment could offer a very meaningful chance to enhance outcomes,” said Dr. Michael Castro, MD, Neuro-oncologist, Medical Oncologist at Beverly Hills Cancer Center; Chief Medical Officer at Cellworks, Group Inc. and Co-Principal Investigator of the study. Cellworks Personalized Therapy Biosimulation The Cellworks Platform biosimulates how a patient's personalized genomic disease model will respond to therapies prior to treatment and can also identify novel drug combinations for treatment-refractory patients. The platform is powered by the groundbreaking Cellworks CBM, a highly curated mechanistic network of 6,000+ human genes, 30,000 molecular species and 600,000+ molecular interactions. 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 predicts the efficacy of specific chemotherapies. Study: ASH Abstract 2171 The purpose of the study was to examine how Differentiation Scoring derived from the Cellworks Platform, Computational Biology Model, and each Myelodysplastic Syndrome patient’s genomic aberrations could serve as a biomarker to predict response to Hypomethylating Agents. Background Differentiation arrest resulting from aberrant methylation represents a key pathogenic and phenotypic feature of MDS. Hypomethylating agents (HMA) can reverse epigenetic dysregulation, but single agents fail to control the disease in approximately 50% of patients, many of whom progress to AML and carry a dismal prognosis. Methods The study included 169 MDS patients treated with azacytidine (n = 86) or decitabine (n = 83) whose genomic aberrations and clinical outcomes were available from public databases. Biosimulation of the disease state was computationally derived from pathways that were up- or down-regulated by individual genomic aberrations. DS was defined as the ratio of the quantified impact of key differentiation biomarkers in myeloid malignancies (CEBPA, GATA1, SPI1 and ITGAM) divided by the impact of HOXA9 transcription, a known repressor of differentiation, and normalized on a log2 scale. The Cellworks Platform and CBM were used to determine the change in DS attributable to HMA to define an efficacy score (ES) as a parameter of drug response. A Pearson correlation coefficient was obtained using the two variables. DS in clinical responders (R) and non-responders (NR) was evaluated with the Student t-test. DS was defined with DS > 1.5 as DS-high and < 1.5 as DS-low. Survival data were available for 101 patients and correlated with DS-high (n=49) and DS-low (n=52) groups using a KM-curve. Results Regarding HMA response, 62 patients were responders, while 107 were non-responders. Prior to therapy, 86 patients had DS-high and 83 had DS-low scores. Post-treatment, DS were correlated with HMA ES (R = 0.58, p < 2.2e-16), and showed a favorable HMA response for DS-high patients. Biosimulation showed the incremental benefit on DS of HMA was greater for people with DS-high than DS-low scores (44% vs 16%, p = 7.51 e-17). Median DS was higher in responders than in non-responders (p=0.00232). Patients with DS-high scores had superior survival compared to those with DS-low scores (log rank p = 0.0016). Different genomic aberrations contributed to the DS scores. DS-high patients had more TP53 mutations, 17p del, 8q amp, and 5q del. On the other hand, DS-low patients more often had mutations in ASXL1, SRSF2, RUNX1, DNMT3A, EZH2, NF1, NRAS, CBL, or 7q deletion. Conclusions This study shows that Cellworks personalized therapy biosimulation, which was based on each patient’s genomic aberrations, reveals a high spectrum of DS among patients with MDS. DS strongly predicted HMA response and in general, non-responders had lower DS and survival than high-DS patients. While patients with DS-low scores might have fared even worse without HMA therapy, this study suggests that DS-low patients should be considered for novel combination therapy at the time of diagnosis given their unsatisfactory outcomes with HMA therapy as a single agent. About Cellworks Group Cellworks Group, Inc. is a leader in Precision Drug Development and Personalized Therapy Biosimulation. The Cellworks Platform predicts therapy response for individual patients and patient cohorts using a breakthrough Computational Biology Model (CBM) and biosimulation technology. Backed by Artiman Ventures, Bering Capital, Sequoia Capital, UnitedHealth Group and Agilent Ventures, Cellworks has the world’s strongest trans-disciplinary team of molecular biologists, cellular pathway modelers and software technologists working toward a common goal – attacking serious diseases to improve the lives of patients. The company is based in South San Francisco, California with a research and development facility in Bangalore, India. For more information, visit . All trademarks and registered trademarks in this document are the properties of their respective owners.