About Dr. Bissan Al-Lazikani
About Dr. Al-Lazikani
Dr. Al-Lazikani is a data scientist and drug discoverer. She applies data science and machine learning to address key challenges in cancer drug discovery and development. Dr. Al-Lazikani has drug discovery experience in both academia and the biotechnology industry. Through this experience, she encountered the myriad of hurdles faced through drug discovery and development pipelines. Dr Al-Lazikani’s research focuses on bringing the power of Data and Artificial Intelligence to address these hurdles, accelerating drug discovery and de-risking innovation. Specifically, she applies data science approaches to integrate multi-disciplinary and multi-modal data to inform all aspects of cancer translational research; and to develop novel machine learning algorithms that learn from these integrated data. Together, her approaches inform decision-making and experimental design throughout the drug discovery and development pipeline. She led the development of the world’s largest public cancer drug discovery platform (canSAR.ai) to inform target selection and prioritization for drug discovery. She now leads the Therapeutics Data Science Initiative at MD Anderson Cancer Center to maximally exploit data to discovery novel drugs and individualize drugs and drug combinations for patients.
Director of Therapeutics Data Science, Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX
Professor, Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX
|1998||MRC Laboratory of Molecular Biology and Newnham College, Cambridge University, Cambridge, GBR, PHD, Structural Computational Biology|
|1995||Imperial College, London, GBR, M.Sc, Computer Science|
|1994||University College, London, GBR, B.Sc, Molecular Biology|
|1999-2001||Howard Hughes Research Fellow, Columbia University, New York City, NY|
Professor, The Institute of Cancer Research, London, 2018 - 2021
Full Faculty, The Institute of Cancer Research, London, 2015 - 2021
Career Development Faculty, The Institute of Cancer Research, London, 2009 - 2005
Chair of Cancer and Drug Discovery Data Science, The Institute of Cancer Research, London, 2018 - 2021
Head of Data Science, The Institute of Cancer Research, London, 2016 - 2021
Chemogenomics Consultant, The European Bioinformatics Institute, Hinxton, Cambridgeshire, 2008 - 2009
Associate Director Discovery Informatics, Inpharmatica Ltd, London, 2001 - 2008
|2023||International Society for Computational Biology Fellow, International Society for Computational Biology|
|2021||Fellow, Royal Society of Biology|
|2021||CPRIT Scholar of Cancer Research|
|2021||Cancer Prevention and Research Institute of Texas Scholar|
|2021||John Black Charitable Foundation-Prostate Cancer Foundation Challenge Award|
|2020||Elected Fellow of the Royal Society of Biology|
|2018||University of London Leading Women Award|
|2016||Victoria and Vinny Smith – Prostate Cancer Foundation Challenge Award|
|2012||American Association of Cancer Research (AACR) Team Science Award|
|2009||Institute of Cancer Research Career Development Faculty Establishment Funds|
|1999||Fellow, Howard Hughes Medical Institute|
|1999||Howard Hughes Postdoctoral Fellowship|
|1995||Medical Research Council PhD Scholarship|
- Al-Tashi Q, Saad MB, Sheshadri A, Wu CC, Chang JY, Al-Lazikani B, Gibbons C, Vokes NI, Zhang J, Lee JJ, Heymach JV, Jaffray D, Mirjalili S, Wu J. SwarmDeepSurv: swarm intelligence advances deep survival network for prognostic radiomics signatures in four solid cancers. Patterns (N Y) 4(8):100777, 2023. e-Pub 2023. PMID: 37602223.
- Antolin AA, Sanfelice D, Crisp A, Villasclaras Fernandez E, Mica IL, Chen Y, Collins I, Edwards A, Müller S, Al-Lazikani B, Workman P. The Chemical Probes Portal: an expert review-based public resource to empower chemical probe assessment, selection and use. Nucleic Acids Res 51(D1):D1492-D1502, 2023. e-Pub 2022. PMID: 36268860.
- di Micco P, Antolin AA, Mitsopoulos C, Villasclaras-Fernandez E, Sanfelice D, Dolciami D, Ramagiri P, Mica IL, Tym JE, Gingrich PW, Hu H, Workman P, Al-Lazikani B. canSAR: update to the cancer translational research and drug discovery knowledgebase. Nucleic Acids Res 51(D1):D1212-D1219, 2023. PMID: 36624665.
- Coker EA, Stewart A, Ozer B, Minchom A, Pickard L, Ruddle R, Carreira S, Popat S, O'Brien M, Raynaud F, de Bono J, Al-Lazikani B, Banerji U. Individualised prediction of drug response and rational combination therapy in NSCLC using artificial intelligence enabled studies of acute phosphoproteomic changes. Mol Cancer Ther 21(6):1020-1029, 2022. e-Pub 2022. PMID: 35368084.
- Antolin AA, Clarke PA, Collins I, Workman P, Al-Lazikani B. Evolution of kinase polypharmacology across HSP90 drug discovery. Cell Chem Biol 28(10):1433-1445.e3, 2021. e-Pub 2021. PMID: 34077750.
- Mitsopoulos C, Di Micco P, Fernandez EV, Dolciami D, Holt E, Mica IL, Coker EA, Tym JE, Campbell J, Che KH, Ozer B, Kannas C, Antolin AA, Workman P, Al-Lazikani B. canSAR: update to the cancer translational research and drug discovery knowledgebase. Nucleic Acids Res 49(D1):D1074-D1082, 2021. PMID: 33219674.
- Workman P, Antolin AA, Al-Lazikani B. Transforming cancer drug discovery with Big Data and AI. Expert Opin Drug Discov 14(11):1089-1095, 2019. e-Pub 2019. PMID: 31284790.
- Wedge DC, Gundem G, Mitchell T, Woodcock DJ, Martincorena I, Ghori M, Zamora J, Butler A, Whitaker H, Kote-Jarai Z, Alexandrov LB, Van Loo P, Massie CE, Dentro S, Warren AY, Verrill C, Berney DM, Dennis N, Merson S, Hawkins S, Howat W, Lu YJ, Lambert A, Kay J, Kremeyer B, Karaszi K, Luxton H, Camacho N, Marsden L, Edwards S, Matthews L, Bo V, Leongamornlert D, McLaren S, Ng A, Yu Y, Zhang H, Dadaev T, Thomas S, Easton DF, Ahmed M, Bancroft E, Fisher C, Livni N, Nicol D, Tavaré S, Gill P, Greenman C, Khoo V, Van As N, Kumar P, Ogden C, Cahill D, Thompson A, Mayer E, Rowe E, Dudderidge T, Gnanapragasam V, Shah NC, Raine K, Jones D, Menzies A, Stebbings L, Teague J, Hazell S, Corbishley C, CAMCAP Study Group, de Bono J, Attard G, Isaacs W, Visakorpi T, Fraser M, Boutros PC, Bristow RG, Workman P, Sander C, TCGA Consortium, Hamdy FC, Futreal A, McDermott U, Al-Lazikani B, Lynch AG, Bova GS, Foster CS, Brewer DS, Neal DE, Cooper CS, Eeles RA. Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets. Nat Genet 50(5):682-692, 2018. e-Pub 2018. PMID: 29662167.
- Antolin AA, Tym JE, Komianou A, Collins I, Workman P, Al-Lazikani B. Objective, Quantitative, Data-Driven Assessment of Chemical Probes. Cell Chem Biol 25(2):194-205.e5, 2018. e-Pub 2017. PMID: 29249694.
- Santos R, Ursu O, Gaulton A, Bento AP, Donadi RS, Bologa CG, Karlsson A, Al-Lazikani B, Hersey A, Oprea TI, Overington JP. A comprehensive map of molecular drug targets. Nat Rev Drug Discov 16(1):19-34, 2017. e-Pub 2016. PMID: 27910877.
- Patel MN, Halling-Brown MD, Tym JE, Workman P, Al-Lazikani B. Objective assessment of cancer genes for drug discovery. Nat Rev Drug Discov 12(1):35-50, 2013. PMID: 23274470.
|Title:||Established Investigator Award|
|Funding Source:||Cancer Prevention & Research Institute of Texas (CPRIT)|
|Title:||The Chemical Probes Portal: An Open Resource Empowering High Quality Chemical Biology|
|Funding Source:||Wellcome Trust Biomedical Resources Grant|
|Title:||Establishment of the canSAR platform at MD Anderson Cancer Center|
|Funding Source:||Lyda Hill|