Parantu Shah, Ph.D.
20 years of experience in cutting-edge of Bioinformatics and Genomics at devising storage solutions, methodology development, building high-throughput analysis environments, and integration and mining of functional- and oncogenomics data.
Expert in statistical modeling and machine learning from ultra-high dimensional biomedical and translational data including next-generation sequencing, microarray, Digital Pathology, Radiomics, RPPA, biomedical texts, DNA and protein sequences and 3D-structures. Demonstrated expertise in statistical modeling of data in high-dimensional settings, variable selection, survival modeling and patient stratification.
Education
MBA Candidate
2023, Questrom School of Business, Boston University, USA General MBA
Ph.D.
2005, European Molecular Biology Laboratory Heidelberg, Germany
- Joint degree with Universidad Autonoma de Madrid, Madrid, Spain
- Concentration: Information Extraction & Data mining from biomedical texts
- Advisor: Peer Bork & Director: Alfonso Valencia Visiting student at the National Institute of Informatics, Tokyo, Japan
- Laboratory PI: Nigel Collier
View Thesis
M. Sc. (by research)
2001, National Center for Biological Sciences, Bangalore, India
- Joint degree with Manipal Academy of Higher Education, Manipal, India
- Concentration: Protein Structural Bioinformatics
- Advisor: R. Sowdhamini
View Thesis
B.Sc. Honors
1998, he Maharaja SayajiRao University of Baroda, Vadodara, India
- Concentration: Chemistry with Physics and Mathematics
Technical Expertise
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20 years of experience in cutting-edge of Bioinformatics and Genomics at devising storage solutions, methodology development, building high-throughput analysis environments, and integration and mining of functional- and oncogenomics data
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Expert in generic (e.g. Python, Perl, C) and statistical (R, MATLAB) programming, database (mySQL, PostgreSQL) and web development (HTML, CSS and JavaScript), AWS infrastructure development and reproducible research (git, Rmarkdown, Jupyter).
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Expert in statistical modeling and machine learning from ultra-high dimensional biomedical and translational data including next-generation sequencing, microarray, Digital Pathology, Radiomics, RPPA, biomedical texts, DNA and protein sequences and 3D-structures.
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Demonstrated expertise in statistical modeling of data in high-dimensional settings, variable selection, survival modeling and patient stratification
Professional Experience
Additional Activities
Research
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Participating in establishment of liquid biopsy, digital pathology/radiomics and lung immunotherapy platforms
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Lead for development of indication agnostic signature from epigenetic biomarker signature with Oxford Biodynamics (data generation, overseeing analysis and interpretation, report & publications)
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Lead for NCI collaboration for genomic biomarkers of response that determine immune function and safety signals
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Part of first in industry collaboration between MD Anderson Apollo platform and EMD Serono that aims to carry out genomics aware, longitudinal data driven clinical trials of various EMD Serono assets.
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Rotation project: development of Bintranfusp alpha trials in TNBC and Cervical cancers
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Rotation project: development of a PCR based CDx assay for patient selection for TNBC trial with Qiagen
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Identification and assessment of vendors/academic collaborators and due diligence
Publications
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45. Oleksiewicz U et al., “KRAB/TRIM28 preserve self-renewal of human pluripotent stem cells through epigenetic repression of pro-differentiation genes” Stem Cell Reports 2017 17 30486-1.
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44. Wiznerowicz M, Shah PK and Andersen, JN “Editorial” Contemp Oncol 2015 19(1A): A78-91.
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43. Baniwal SK, Shah PK, Shi Y, Haduong JH, DeClerck YA, Gabet Y and Frenkel B, “Runx2 promotes both osteoblastogenesis and novel osteoclastogenic signals in ST2 mesenchymal progenitor cells” Osteoporosis International 2011.
Conference Proceedings
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Mrowiec et al., “Digital pathology to evaluate PD-L1 IHC scoring as a predictor of outcome with second-line avelumab treatment in patients with non-small cell lung cancer”. ASCO 2020
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Wolfe CM et al., “Enabling digital image analysis-based translational research with clinical legacy tissue scans” Submitted to ESDP 2020
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Alimzhanov M et al., “Induction of immunogenic cell death and interferon signaling by Carboplatin and the ATR inhibitor M6620 may contribute to anti-tumor activity of M6620-Carboplatin-Avelumb triplet combination in MC38 tumor model” AACR 2020
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Shah PK* et al, Development and validation of baseline predictive biomarkers for response to avelumab in second-line (2L) non-small cell lung cancer (NSCLC) Journal of ImmunoTherapy of Cancer SITC 2019