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Journal Articles

AraC-Daunorubicin-Etoposide (ADE) Response Prediction in Pediatric AML Patients Using a Computational Biology Modeling (CBM) Based Precision Medicine Workflow

Christopher R. Cogle, MD, Taher Abbasi, MS, MBA, Neeraj Kumar Singh, B.Tech, Mohammed Sauban, B.E, Rahul K Raman, M.Sc., Robinson Vidva, B.Tech, Anuj Tyagi, M.Sc., Anay Ashok Talawdekar, M.Tech, Arko Das, M.Sc., Steven M. Kornblau, MD, Fieke W Hoff, BSc, Terzah M. Horton, MD PhD, Shireen Vali, PhD

Blood (2018) 132 (Supplement 1): 4034.

https://doi.org/10.1182/blood-2018-99-115775

Published: 2018

Journal Articles

Analysis of the Evolving MDS/AML Clones to Identify Resistance Mechanisms and Predict New Therapy Options at Relapse Using Computational Biology Modeling: Case-Studies from iCare1 Clinical Study

Shireen Vali, PhD, Taher Abbasi, MS, MBA, Neeraj Kumar Singh, B.Tech, Shahabuddin Usmani, M.Sc., Deepak Anil Lala, B.Tech, Poornachandra G, B.Tech, Saumya Radhakrishnan, B.Tech, Shivgonda C Birajdar, MCA, Ganesh Naga, B.Tech, Leylah M. Drusbosky, PhD, Christopher R. Cogle, MD

Blood (2018) 132 (Supplement 1): 3086.

https://doi.org/10.1182/blood-2018-99-115821

Published: 2018

Journal Articles

Azacitidine Response Prediction in MDS Patients with NGS Data Using a Computational Biology Modeling (CBM) Based Clinical Decision Support System

Lubomir Minarik, MD, Leylah M. Drusbosky, PhD, Taher Abbasi, MS, MBA, Karina Vargova, MBBS, MSc, Vojtech Kulvait, PhD, Anna Jonasova, MD, Neeraj Kumar Singh, B.Tech, Yashaswini S Ullal, B.E, Sirisha Narayanabhatia, M.Sc., Aktar Alam, BCA, Kunal Ghosh Roy, M.Sc., Ashish Choudhary, M.Sc., Shireen Vali, PhD, Christopher R. Cogle, MD, Tomas Stopka, MD PhD

Blood (2018) 132 (Supplement 1): 3087.

https://doi.org/10.1182/blood-2018-99-114610

Published: 2018

Journal Articles

Computational Modelling of Multiple Myeloma Patient Genomic Signatures to Predict Treatment Outcome

Aneel Paulus, MD, Prachi Jani, MD, Salman Ahmed, MD, Sonikpreet Aulakh, MD, Alak Manna, PhD, Neeraj Kumar Singh, B.Tech, Mohammed Sauban, B.E, Zakir Husain, M.Tech, Ansu Kumar, M.Sc., Pallavi Kumari, M.Sc., Anuj Tyagi, M.Sc., Taimur Sher, MD, Rami Manochakian, MD, Vivek Roy, MD, Taher Abbasi, MS, MBA, Shireen Vali, PhD, Asher A. Chanan-Khan, MD, Sikander Ailawadhi

Blood (2018) 132 (Supplement 1): 1911.

https://doi.org/10.1182/blood-2018-99-119574

Published: 2018

Journal Articles

Mechanisms of Azacitidine Chemotherapy Resistance in AML and MDS and New Therapy Options

Lubomir Minarik, MD, Leylah M. Drusbosky, PhD, Taher Abbasi, MS, MBA, Karina Vargova, MBBS, MSc, Vojtech Kulvait, PhD, Anna Jonasova, MD, Neeraj Kumar Singh, B.Tech, Chandan Kumar, M.Tech, Rakhi Purushothaman Suseela, B.Tech, Mamatha Patil, B.E, Patil Nilesh Dattatraya, M.Sc., Krishna Kumar Tiwari, B.Tech, Shireen Vali, PhD, Christopher R. Cogle, MD, Tomas Stopka, MD PhD

Blood (2018) 132 (Supplement 1): 5506.

https://doi.org/10.1182/blood-2018-99-114466

Published: 2018

Journal Articles

Predicting Carfilzomib Resistance Mechanisms and Therapeutics Using Computational Modelling of Genomics and Proteomics

Andrej Besse, M.Sc, Christopher R. Cogle, MD, Leylah M. Drusbosky, PhD, Shireen Vali, PhD, Taher Abbasi, MS, MBA, Neeraj Kumar Singh, B.Tech, Neha G Gupta, M.Sc., Abha Kushwaha, M.Sc., Pallavi Kumari, M.Sc., Karthik Sundara Raju, M.Sc., Ganesh Naga, B.Tech, Sayani Basu, M.Tech, Christoph Driessen, MD, Lenka Besse, PhD

Blood (2018) 132 (Supplement 1): 3193.

https://doi.org/10.1182/blood-2018-99-116939

Published: 2018

Journal Articles

WT1 and BCORL1 Identified By Computational Biology Modeling Analysis of Patient Genomics Are Novel Predictors of Response to Azacitidine (AZA) and Lenalidomide (LEN) Treatment in Acute Myeloid Leukemia (AML)

Brett M Stevens, PhD, Amanda Winters, MDPhD, Taher Abbasi, MS, MBA, Neeraj Kumar Singh, B.Tech, Yashaswini S Ullal, B.E, Ilu Kumari, M.Sc., Anuj Tyagi, M.Sc., Aftab Alam, M.Sc., Neelesh Lunkad, M.Tech, Leylah M. Drusbosky, PhD, Christopher R. Cogle, MD, Shireen Vali, PhD, Daniel A Pollyea, MD

Blood (2018) 132 (Supplement 1): 1538.

https://doi.org/10.1182/blood-2018-99-114429

Published: 2018

Journal Articles

Predictive Analysis on Prognostic Impact of Monosomy 7 in AML and Identified Therapy Options for This Cohort

Shireen Vali, PhD, Christopher R. Cogle, MD, Neeraj Arora, MD, Krishnan Shekhar, PhD, Mammen Chandy, MD, Manju Sengar, MD DM, Hasmukh Jain, MD DM, Girish Chinnaswamy, MD MRCP, Neeraj Kumar Singh, B.Tech, Shahabuddin Usmani, M.Sc., Anusha Pampana, M.Sc., Vijayashree P Shyamasundar, M.Sc., Huzaifa Sikora, B.Tech, Ansu Kumar, M.Sc., Taher Abbasi, MS, MBA, Vivek S Radhakrishnan, MDDM,MSc

Blood (2018) 132 (Supplement 1): 1539.

https://doi.org/10.1182/blood-2018-99-116603

Published: 2018

Journal Articles

Predicting Response to BET Inhibitor in Combination with Palbociclib / Sorafenib Using a Computational Model and Its Validation: A Beat AML Project Study

Jeffrey W. Tyner, PhD, Brian J. Druker, MD, Stephen E Kurtz, PhD, Cristina E. Tognon, PhD, Leylah M. Drusbosky, PhD, Robinson Vidva, B.Tech, Yugandhara Narvekar, M.Sc., Ashish Kumar Agrawal, B.V.Sc, A.H., Saji Gera, M.Tech, Samiksha Avinash Prasad, M.Sc., Vijayashree P Shyamasundar, M.Sc., Gaurav Singh Tunwer, M.Sc., Taher Abbasi, MS, MBA, Shireen Vali, PhD, Christopher R. Cogle, MD

Blood (2018) 132 (Supplement 1): 1540.

https://doi.org/10.1182/blood-2018-99-115284

Published: 2018

Journal Articles

Predicting Response to Dasatinib Using a Computational Model and Its Validation: A Beat AML Project Study

Jeffrey W. Tyner, PhD, Brian J. Druker, MD, Cristina E. Tognon, PhD, Stephen E Kurtz, PhD, Leylah M. Drusbosky, PhD, Diwyanshu Sahu, M.Sc., Robinson Vidva, B.Tech, Shweta Kapoor, M.Sc., Humera Azam, M.Sc., Rajeev Kumar, B.Tech, Padmagiri G Chickdipatti, B.E, Nithya T Raveendaran, M.Tech, Reshma P Gopi, M.Sc., Taher Abbasi, MS, MBA, Shireen Vali, PhD, Christopher R. Cogle, MD

Blood (2018) 132 (Supplement 1): 1541.

https://doi.org/10.1182/blood-2018-99-115678

Published: 2018

Journal Articles

Clinical Validation of Treatment Response Predictions Using a Genomics Driven Computational Biology Modelling Multiple Myeloma Algorithm

Ravi Vij, MBBS, Justin King, Mark A. Fiala, BS, Neeraj Kumar Singh, B.Tech, Mohammed Sauban, B.E, Zakir Husain, M.Tech, Anjanasree V Lakshminarayana, B.E, Anay Ashok Talawdekar, M.Tech, Upasana Mitra, M.Sc., Taher Abbasi, MS, MBA, Shireen Vali, PhD

Blood (2018) 132 (Supplement 1): 1893.

https://doi.org/10.1182/blood-2018-99-118686

Published: 2018

Journal Articles

Predictive Simulation Modeling in JAK2-Mutant MPNs Identified Ruxolitinib and Sorafenib As a Synergistic Drug Combination for Disease Modifying Therapy

Peter P. Sayeski, PhD, Leylah M. Drusbosky, PhD, Neeraj Kumar Singh, B.Tech, Anusha Pampana, Shahabuddin Usmani, MS, Mohammed Sauban, BE, Abha Kushwaha, Anu Ramakrishnan, Taher Abbasi, MS, MBA, Shireen Vali, PhD, Christopher R. Cogle, MD

Blood (2017) 130 (Supplement 1): 5287.

https://doi.org/10.1182/blood.V130.Suppl_1.5287.5287

Published: 2017

Journal Articles

Predicting Mechanisms of Ibrutinib-Resistance in Chronic Lymphocytic Leukemia (CLL) Using Computational-Based Modeling for Personalized Therapy with Clinical Validation

Leylah M. Drusbosky, PhD, Aneel Paulus, MD, Anne Quillet Mary, PhD, Loic Ysebaert, MD PhD, Ansu Kumar, MS, Neeraj Kumar Singh, B.Tech, Yashaswini Ullal, BE, Priyanka Bhargav, BE, Humera Azam, MS, Taher Abbasi, MS, MBA, Shireen Vali, PhD, Asher A. Chanan-Khan, MD, Christopher R. Cogle, MD

Blood (2017) 130 (Supplement 1): 4278.

https://doi.org/10.1182/blood.V130.Suppl_1.4278.4278

Published: 2017

Journal Articles

Predicting Response to IDH1/IDH2 Inhibitors Beyond IDH Mutations Using a Computational Model and Its Validation: A Beat AML Project Study

Leylah M. Drusbosky, PhD, Robinson Vidva, BT, Saji Gera, MT, Arko Das, MS, Krishna K Tiwari, BT, Vishwas Joseph, MS, Subrat Mohapatra, MS, Neelesh Lunkad, MT, Taher Abbasi, MS, MBA, Shireen Vali, PhD, Cristina E. Tognon, PhD, Stephen E Kurtz, PhD, Jeffrey W. Tyner, PhD, Brian J. Druker, MD, Christopher R. Cogle, MD

Blood (2017) 130 (Supplement 1): 3907.

https://doi.org/10.1182/blood.V130.Suppl_1.3907.3907

Published: 2017

Journal Articles

Predicting Response to BET Inhibitors Using a Computational Model and Its Validation: A Beat AML Project Study

Leylah M. Drusbosky, PhD, Robinson Vidva, BT, Saji Gera, MT, Anjanasree V. Lakshminarayana, BE, Vijayashree P. Shyamasundar, MS, Ashish Kumar Agrawal, BS, Anay Talawdekar, MT, Taher Abbasi, MS, MBA, Shireen Vali, PhD, Cristina E. Tognon, PhD, Stephen E Kurtz, PhD, Jeffrey W. Tyner, PhD, Brian J. Druker, MD, Christopher R. Cogle, MD

Blood (2017) 130 (Supplement 1): 3908.

https://doi.org/10.1182/blood.V130.Suppl_1.3908.3908

Published: 2017

Journal Articles

Predicting Response to CDK4/6 Inhibitors and Combinations Using a Computational Biology Model and Its Validation: A Beat AML Project Study

Leylah M. Drusbosky, PhD, Madeleine Turcotte, MS, Paul Castillo, MD, Robinson Vidva, BT, Saji Gera, MT, Mohammed Sauban, BE, Priyanka Bhargav, BE, Punya Deep, MS, Shweta Kapoor, MS, Taher Abbasi, MS, MBA, Shireen Vali, PhD, Cristina E. Tognon, PhD, Stephen E Kurtz, PhD, Jeffrey W. Tyner, PhD, Brian J. Druker, MD, Christopher R. Cogle, MD

Blood (2017) 130 (Supplement 1): 3909.

https://doi.org/10.1182/blood.V130.Suppl_1.3909.3909

Published: 2017

Journal Articles

Digital Drug Screening and Computational Modeling Identifies Treatment Opportunities Despite Lack of Directly Actionable Mutations in Acute Myeloid Leukemia (AML) and Myelodysplastic Syndromes (MDS)

Blood (2017) 130 (Supplement 1): 3910.

https://doi.org/10.1182/blood.V130.Suppl_1.3910.3910

Published: 2017

Journal Articles

Computational Biology Approach to Predict Hypomethylating Agent (HMA) Response Using Genomic and Clinical Characteristics in Myelodsyplastic Syndromes (MDS)

Leylah M. Drusbosky, PhD, Salah-Eddin Komrokji, Najla Al Ali, M.Sc, Neeraj Kumar Singh, B.Tech, Chandan Kumar, MT, Sumanth Vasista, BE, Diwyanshu Sahu, M.Sc., Ganesh Naga, BT, Patil Dattatraya, MS, Taher Abbasi, MS, MBA, Shireen Vali, PhD, David A Sallman, MD, Rami S. Komrokji, MD, Christopher R. Cogle, MD

Blood (2017) 130 (Supplement 1): 2954.

https://doi.org/10.1182/blood.V130.Suppl_1.2954.2954

Published: 2017

Journal Articles

Personalized Therapy Design for Early T-Cell Precursor Acute Lymphoblastic Leukemia (ETP-ALL) Using Computational Biology Modeling with in Vitro Validation

Madeleine Turcotte, MS, Raphael Charles Bosse, BS, MD PhD, Kimberly E. Hawkins, PhD BS, Amy Meacham, MS, Vindhya Vijay, MS, Girish Chinnaswamy, MD MRCP, Manju Sengar, MD DM, Ansu Kumar, MS, Shwetha K, BE, Anisha Kamath, BT, Anjana T. Nair, MS, Karthik S. Raju, MS, Taher Abbasi, MS, MBA, Shireen Vali, PhD, Christopher R. Cogle, MD, Leylah M. Drusbosky, PhD

Blood (2017) 130 (Supplement 1): 1448.

https://doi.org/10.1182/blood.V130.Suppl_1.1448.1448

Published: 2017

Journal Articles

Computational Biology Model of ETP-ALL Used to Accurately Classify ETP-ALL Vs Non ETP-ALL Patients with Genomic Input

Leylah M. Drusbosky, PhD, Ansu Kumar, MS, Shwetha K, BE, Sumanth Vasista, BE, Anuj Tyagi, MS, Swaminathan Rajagopalan, MT, Aftab Alam, MS, Taher Abbasi, MS, MBA, Shireen Vali, PhD, Girish Chinnaswamy, MD MRCP, Manju Sengar, MD DM, Bijal D. Shah, MD, Christopher R. Cogle, MD

Blood (2017) 130 (Supplement 1): 1449.

https://doi.org/10.1182/blood.V130.Suppl_1.1449.1449

Published: 2017

NARROW

AraC-Daunorubicin-Etoposide (ADE) Response Prediction in Pediatric AML Patients Using a Computational Biology Modeling (CBM) Based Precision Medicine Workflow

Analysis of the Evolving MDS/AML Clones to Identify Resistance Mechanisms and Predict New Therapy Options at Relapse Using Computational Biology Modeling: Case-Studies from iCare1 Clinical Study

Azacitidine Response Prediction in MDS Patients with NGS Data Using a Computational Biology Modeling (CBM) Based Clinical Decision Support System

Computational Modelling of Multiple Myeloma Patient Genomic Signatures to Predict Treatment Outcome

Mechanisms of Azacitidine Chemotherapy Resistance in AML and MDS and New Therapy Options

Predicting Carfilzomib Resistance Mechanisms and Therapeutics Using Computational Modelling of Genomics and Proteomics

WT1 and BCORL1 Identified By Computational Biology Modeling Analysis of Patient Genomics Are Novel Predictors of Response to Azacitidine (AZA) and Lenalidomide (LEN) Treatment in Acute Myeloid Leukemia (AML)

Predictive Analysis on Prognostic Impact of Monosomy 7 in AML and Identified Therapy Options for This Cohort

Predicting Response to BET Inhibitor in Combination with Palbociclib / Sorafenib Using a Computational Model and Its Validation: A Beat AML Project Study

Predicting Response to Dasatinib Using a Computational Model and Its Validation: A Beat AML Project Study

Clinical Validation of Treatment Response Predictions Using a Genomics Driven Computational Biology Modelling Multiple Myeloma Algorithm

Predictive Simulation Modeling in JAK2-Mutant MPNs Identified Ruxolitinib and Sorafenib As a Synergistic Drug Combination for Disease Modifying Therapy

Predicting Mechanisms of Ibrutinib-Resistance in Chronic Lymphocytic Leukemia (CLL) Using Computational-Based Modeling for Personalized Therapy with Clinical Validation

Predicting Response to IDH1/IDH2 Inhibitors Beyond IDH Mutations Using a Computational Model and Its Validation: A Beat AML Project Study

Predicting Response to BET Inhibitors Using a Computational Model and Its Validation: A Beat AML Project Study

Predicting Response to CDK4/6 Inhibitors and Combinations Using a Computational Biology Model and Its Validation: A Beat AML Project Study

Digital Drug Screening and Computational Modeling Identifies Treatment Opportunities Despite Lack of Directly Actionable Mutations in Acute Myeloid Leukemia (AML) and Myelodysplastic Syndromes (MDS)

Computational Biology Approach to Predict Hypomethylating Agent (HMA) Response Using Genomic and Clinical Characteristics in Myelodsyplastic Syndromes (MDS)

Personalized Therapy Design for Early T-Cell Precursor Acute Lymphoblastic Leukemia (ETP-ALL) Using Computational Biology Modeling with in Vitro Validation

Computational Biology Model of ETP-ALL Used to Accurately Classify ETP-ALL Vs Non ETP-ALL Patients with Genomic Input

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American Society of Hematology

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ASH Publications

American Society of Hematology

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