Key Responsibilities:Utilize novel analytical methods applied to multi-modal data - such as genomic (bulk, single cell, spatial), imaging, and clinical - to identify targets in patient sub-populationsIn partnership with Tempus’ modeling lab, use data from CRISPR and cell perturbation experiments in patient-derived organoids to identify and validate novel targetsDevelop and implement scientific strategies and experimental work plans, including identifying new methodologies and approaches for large clinicogenomic databases and PDOsIntegrate the above to prioritize target opportunities matched to biomarker and indication strategies that enhance likelihood of developmental success.Mentor and project manage a team of junior scientists to deliver on the project goals and objectives Communicate the scientific and technical plans and outcomes to a cross-functional group of project and senior leadership stakeholders, both internal and at biopharma partnersWork closely with other cross-functional teams across the R&D and broader Tempus organization (product engineering, operations, clinical genomics labs, medical, science, data science, etc) to integrate work plans and approachesFoster a collaborative and inclusive work environment, promoting interchange of expertise between Tempus and biopharma partner contributors, and driving creativity, innovation, and scientific excellence.

● Developed bioinformatics algorithms using R programming and Python, enabling the extraction of actionable insights from complex clinical trial, electronic health records, and genomic assay data, driving evidence-based decision-making. ● Leveraged expertise in advanced statistical and bioinformatics analysis to analyze 10+ multi-omics datasets, specifically transcriptomic and single cell sequencing data. Utilized cutting-edge methodologies to identify promising targets and candidate selection to support 3 antibody-drug conjugate pre-exploratory programs, enabling the discovery of novel therapeutic strategies.● Launched and deployed an advanced machine learning and statistical modeling framework to analyze genomic data from internal clinical trials and 3000+ real-world patient records; identified key genomic features associated with response to antibody-drug conjugates (ADCs) and immune checkpoint inhibitors. ● Led the successful implementation of advanced deep learning workflows in Python Jupyter notebooks, integrating and analyzing 'omics datasets to generate single cell atlases from more than 1 million cells. This approach enabled the identification of cell type-specific drug response signatures, comprehensive evaluation of antibody drug target specificity, and thorough assessment of potential off-target effects, advancing research capabilities.● Trained statistical models and neural networks to identify key genomic features impacting tumor outcome using public, internal clinical genomics data, and real-world evidence from Tempus AI/Labs; implemented Variational Autoencoders for transfer learning, data dimensionality reduction and enhanced predictive accuracy.● Participated in due diligence efforts with 3 biotech industry partners including AI solution deals, supporting the acquisition of critical data resources to drive data-driven insights for research exploratory and pipeline projects.

● Implemented statistical and predictive modeling with R and Python to extract actionable features associated with patient response to targeted therapies and standard of care from complex clinical trial biomarker data including ctDNA from Predicine, Guardant Health, Foundation Medicine (FMI), genomic tissue bulk and single cell assays, cell lines screens, in vivo PDX assays, public datasets (DEPMAP, TCGA, etc.) and real-world evidence from Flatiron Health and FMI, driving evidence-based decision-making. ● Orchestrated and streamlined reverse translation efforts for solid tumor signaling franchise as group leader and bioinformatics lead scientist; achieved breakthroughs in target discovery and combination strategies through successful exploration of PI3K inhibitor clinical trials (INAVO120, Sandpiper, Lorelei, Morpheus) by identifying PI3Ka inhibitor and degrader inavolisib can co-opt FGFR2 to enhance response in hormone receptor-positive breast cancer patients. ● Led 5+ cross-functional collaboration with Research, Translational Medicine, Biomarker, Early Clinical development, and Informatics team leads to drive adoption of bioinformatics data-derived insights, resulting in accelerated decision-making across the organization for improved patient outcomes.● Presented research findings on the effectiveness of PI3K inhibitors and endocrine therapies in breast cancer at international conferences.● Spearheaded the recruitment, development, and management of a talented team of 1 senior bioinformatics scientist and 1 contractor, driving the solid tumor signaling franchise's reverse translation capabilities and data derived insights.● Mentored 1 intern in executing research project leveraging statistics and reverse translation to extract digital pathology features associated with treatment Taselisib response in Sandpiper Phase 3 trial through multi-modal analysis of omics data and digital pathology PathAI extracted features.

● Conducted comprehensive analysis of 10+ large-scale NGS omics bulk and single cell datasets, high-dimensional assay, and drug sensitivity data from diverse sources (internal, public, commercial) to identify optimal drug combinations, biomarkers, and tumor resistance mechanisms; delivered crucial insights to drive precision medicine advancements.● Led Bioinformatics analysis of 10+ complex datasets to unravel intricate biological pathways and identify novel therapeutic targets; facilitated cross-functional collaboration and knowledge sharing to accelerate drug discovery and development efforts.● Led 1 research project focused on investigating the impact of ARID1A gene mutations on cetuximab resistance in first-line metastatic colorectal cancer patients, contributing to a deeper understanding of treatment response and paving the way for personalized therapies. ● Developed an innovative gene expression–based prognostic signature for isocitrate dehydrogenase (IDH) wild-type glioblastoma, leveraging clinical trial datasets representative of glioblastoma clinical trial populations, fostering collaboration, and driving advancements in precision medicine.● Awarded the prestigious Genentech Innovation Fund in 2019 as co-primary applicant to establish novel single nuclei methylation technology, leveraging cutting-edge research in the field; managed a 1 wet-bench contractor to develop and optimize a new assay, driving our innovation award forward.

● Translated complex molecular biomarker data into diagnostic tools; guided understanding of drug activity in patient tumors and identified subsets of patients for targeted therapeutic interventions, from for 2 gastrointestinal and 3+ breast cancer clinical trial and omics dataset.● Collaborated on biomarker projects with OBD on breast cancer (Neosphere study) and colorectal cancer (CALGB 80405 trial), and GBM (ARTE, TAMIGA, EORTC 26101, AVAglio, GLARIUS trials).● Awarded a highly competitive Genentech Innovation Fund in 2018, to support a collaboration between Genentech and the Metrakos Lab at McGill University to adapt the Cao et al., 2017, Science paper to enable the simultaneous measurement of single nuclei RNA and DNA from colorectal cancer patient biopsies.

Translation of complex molecular biomarker data into useful diagnostic tools to guide our understanding of drug activity in patient tumors and identify subsets of patients who may benefit from specific therapeutic interventions.Weighted Gene co-expression analysis to identify signature associated with response in the NeoSphere Trial.

● Led large-scale data processing and analysis of 10+ projects for researchers Dr. Morag Park, Dr. Russell Jones, and Dr. Peter Siegel at McGill University and international collaborations, using genomics, microarray, and metabolomics data. ● Managed secure storage and regular backups for all NGS sequencing data on our lab servers, ensuring data integrity and availability for analysis processes on Compute Canada Calcul Quebec clusters.● Created lecture courses for Dr. Nicole Beauchemin's GCRC bioinformatics workshops and EXMD 635 course, covering a wide range of topics such as Microarrays & next generation sequencing pre-processing and analysis, experimental design, interpreting gene expression data, aligning genes to the genome, and pathway analysis.

Responsible for developing content for medical and pharmaceutical training activities.Research, create, and edit medical/scientific deliverables in various scientific and therapeutic areasPerform scientific literature searches. Produce high-quality content quickly and efficiently to meet deadlines.Maintain familiarity with current industry practices and regulatory requirements.Ensure document content and style adheres to appropriate regulatory guidelines and complies with departmental SOPs and style guidelines.

● Defined and directed two independent research projects analyzing leukemia-specific transcriptional changes and minimal residual disease markers in Acute Myeloid Leukemia. ● Led the development and implementation of highly efficient bioinformatics pipelines, leveraging R, Perl, BASH, and Python to quantify splicing variants from NGS data. Facilitated precise analysis of patient data, uncovering correlations with survival, drug response, and chemical compounds. ● Presented research findings at regular meetings and conferences, communicating complex scientific concepts to diverse audiences.● Trained summer students in the lab of Dr. Brian Wilhelm, enhancing their research skills and fostering their professional development. ● Co-authored Mastering Scientific Computing with R, published by PACKT Publishing, where I contributed 5 chapters covering Programming with R, Statistical Methods, Linear Models, Simulations and Monte Carlo Modeling, and Optimization with R. Collaborated closely with Dr. Paul Gerrard to deliver practical insights for readers seeking to excel in scientific computing. https://www.packtpub.com/authors/radia-johnson.

Roles & Responsibilities: Designed experimental assays to study the molecular and cellular consequences of JAK2 mutations in hematological malignancies. Prepared blood samples from patients for processing and set up sequencing assays. Analyzed data from high-throughput assays with R.

Lab demonstrator and marker for IMM435F Practical Immunology course at the University of Toronto.• Trained and managed a group of 13 immunology 4th year undergraduate students • Supervised students execution of lab experiments and marked the relevant lab reports. • Challenged lab students with questions related to the ongoing experiments

Teaching Assistant for the IMM250H1 Infection & Immunity course at the University of Toronto. • Marked exams and term paper and invigilated final exam. Seminar Leader for the Immunology for 2nd Year Medical students Pathobiology of Disease Immunology Section at the University of Toronto. • Presented reviews of material taught in class and answer student questions.