Derick Hoskinson, PhD
Clinical Scientist & Lead Developer
I am a senior clinical scientist with extensive experience in genomic data analysis, variant classification and the development of clinical genetic testing panels. My work sits at the intersection of genomic analysis and clinical reporting
With a PhD in Genetics from Tufts University and years of hands-on experience at Tempus AI, Harvard Medical School, I have contributed to FDA submissions, developed cancer assays, and led a team of variant scientists
I am keen to leverage my expertise in variant classification, data wrangling & analysis and clinical reporting to build tools, products, and guidelines to support patients through precision medicine
Professional Experience
A timeline of my contributions to clinical genomics.
Senior Clinical Scientist
2019 – Present- Defined clinical reporting requirements for SNV/indels, copy number variants, and structural variants for Tempus xH assay.
- Created a tailored bed file to optimize genomic data analysis and facilitate the identification, classification, and clinical reporting of genetic variants on a large gene panel, resulting in improved accuracy and efficiency of downstream analysis.
- Contributed to the development and submission of the xT CDx assay to the FDA by curating and analyzing gene data to rank evidence per gene, ensuring accurate and effective clinical use.
- Played a vital role in the development and application of a new hereditary genetic testing panel, Tempus, xGv3 to identify germline variants in genes associated with hereditary cancer syndromes and incidental findings.
- Identified gaps and deficiencies in current workflows and executed new workflows and SOPs to harmonize variant classification across multiple institutions.
- Spearheaded the development and implementation of a reportable bed file solution for the Tempus xF assay, allowing for targeted reporting of specific genomic regions and improving the overall quality of data analysis.
- Used R programming language to design and implement a regions of interest bed file for reporting insertions and deletions for Tempus xF assay.
- Used R programming language to create, update, and modify curated data to justify the inclusion or exclusion of genomic regions for xT-oncology FDA application.
- Acted as the scientific lead in the development of the Tempus xF liquid biopsy panel to sequence and report SNVs and indels in clinically relevant regions of 105 genes plus CNVs and DNA rearrangements in a subset of these genes.
- Used R programming language to programmatically access data, wrangle data, analyze data and present data to implement changes in workflow or other internal processes.
Clinical Scientist
2017 – 2019- Evaluated data and analyzed variants for a project that led to the publication of the results in Nature BioTechnology.
- Trained over 20 M.A.s, Ph.D.s, and post-baccalaureates in germline and somatic variant classification.
- Worked closely with colleagues to build a team of variant scientists from 2 individuals to over 20 highly skilled variant scientists.
- Gained proficiency in the R programming language and experience using Python, JavaScript, HTML, and CSS.
Clinical Knowledge Curation Coordinator
2015 – 2017- Trained over 25 M.Ds, M.D./Ph.D.s, rotating fellows, undergraduates, and post-baccalaureates in constitutional variant classification.
- Assessed pathogenicity of variants from large gene panels covering cardiomyopathy, hearing loss, pulmonary disease, and Noonan syndrome.
- Evaluated data and assessed variants as a critical member of the Geisinger MyCode project including the 56 genes recommended by the ACMG and 20 additional genes from Geisinger.
- Extensive experience with population databases (1000 genomes, ESP, ExAC, gnomAD).
- Proficient in the use of variant databases including HGMD, ClinVar, LOVD, Deafness Variation database, Cardiodb, MitoMap, Leiden Muscular Dystrophy database, ARUP and COSMIC.
Medical Writer II
2014 – 2015- Wrote evidence-based summaries of clinical trials aimed at serving as a resource for physicians and other health care professionals at the point of care.
- Wrote evidence-based point-of-care references for a number of clinically important disease topics.
- Critically assessed published clinical trials for methodological integrity.
- Critically assessed published clinical trials for inclusion in the DynaMed database in areas such as oncology, cardiology, infectious disease, endocrinology, and pediatrics.
- Applied in-depth knowledge of statistical methods to critically appraise clinical trials.
- Extensively worked in an XML environment to deliver point-of-care clinical information.
Technical Expertise
Navigating the complexity of biology with the precision of engineering.
Core Expertise
Clinical Variant Interpretation
- ACMG/AMP variant classification
- Somatic vs germline variant interpretation
- Tumor-only and matched Tumor-normal analysis
- Copy number and structural variant interpretation
- Fusion breakpoint and isoform analysis
- Variant pathogenicity evidence synthesis
- Gene-disease validity assessment
- Loss of function vs gain of function mechanism assessment
- Variant reclassification workflows
Clinical Genomics and Oncology
- Molecular oncology and cancer biology
- Hematologic and solid tumor genomics
- Gene panel design and optimization
- Biomarker actionability assessment
- Companion Diagnostic (CDx) development
- Translational research support
Evidence evaluation and curation
- Primarly literature review and critical analysis
- Mechanism of disease evidence synthesis
- Functional assay interpretation
- Population frequency and penetrance assessment
- Clinical Validity and clinical utility assessment
- Consensus guideline interpretation (ACMG, AMP, NCCN)
- Evidence gap analysis and prioritization
Regulatory & Quality
- FDA Submission support (CDx)
- Analytical and clinical validation support
- SOP authorship and review
- CAP/CLIA compliance
- Cross-functional collaboration (laboratory, bioinformatics, regulatory
Leadership & Collaboration
- Cross team scientific leadership
- Mentorship of junior scientists
- Stackholder Communication (clinical, regulatory, reporting)
Tools & Databases
Variant & Clinical Knowledgebases
- ClinVar
- OncoKB
- COSMIC
- gnomAD
- HGMD
- UniProt
Literature and Evidence Sources
- PubMed / PubMed Central
- NCCN guidelines
- FDA Drug Lables
Genomic Resources
- MANE Select transcripts
- UCSC Genome Browser
- IGV
- Ensembl & RefSeq
- Internal LIMS and Knowledgebases
- Assay design and reporting pipelines
Programming & Computational Skills
languages
- R (data wrangling, analysis and visualization)
- Python (Data wrangling analysis and visualization)
- Typescript
- SQL (PostgreSQL)
Web development
- React 19
- Next.js (App Router, server components, server actions)
- Tailwind CSS
- MDX-based content systems
- Responsive and printable document generation
- Prisma ORM
- PubMed / NCBI API integration
- RAG pipeline for scientific documents
- OpenAI & Gemini coding
Data Prcoessing
- XML parsking and transformation
- Large-scale literature ingestion
Work Projects
Highlighting impact in clinical work
xT CDx FDA Submission
Regulatory & Compliance
Orchestrated the identification and ranking of evidence for the xT CDx assay submission to the FDA. Curated gene lists and ensured clinical validity of the NGS panel.
xH: Tempus Whole Genome Assay - Hematological Assay
Product Development
Key contributor to the whole genome sequencing assay xH. Designed to detect hematological variants with high sensitivity and specificity
Selected Publications
Peer-reviewed research in clinical genomics, variant interpretation, and molecular biology.
Mutations in yeast Pcf11, a conserved protein essential for mRNA 3' end processing and transcription termination, elicit the Environmental Stress Response
Graber JH, Hoskinson D, Liu H, Kaczmarek Michaels K, Benson PS, Maki NJ, Wilson CL, McGrath C, Puleo F, Pearson E, Kuehner JN, Moore C
Tumor Mutational Burden From Tumor-Only Sequencing Compared With Germline Subtraction From Paired Tumor and Normal Specimens
Parikh K, Huether R, White K, Hoskinson DC, Beaubier N, Dong H, Adjei AA, Mansfield AS
Integrated genomic profiling expands clinical options for patients with cancer
Beaubier N, Bontrager M, Huether R, Igartua C, Lau D, Tell R, Bobe AM, Bush S, Chang AL, Hoskinson DC, Khan AA, Kudalkar E, Leibowitz BD, Lozachmeur A, Michuda J, Parsons J, Perera JF, Salahudeen A, Shah KP, Taxter T, Zhu W, White KP
Considerations for clinical curation, classification, and reporting of low-penetrance and low effect size variants associated with disease risk
Senol-Cosar O, Schmidt RJ, Qian E, Hoskinson DC, Mason-Suares H, Funke B, Lebo MS
Exome Sequencing-Based Screening for BRCA1/2 Expected Pathogenic Variants Among Adult Biobank Participants
Manickam K, Buchanan AH, Schwartz MLB, Hallquist MLG, Williams JL, Rahm AK, Rocha H, Savatt JM, Evans AE, Butry LM, Lazzeri AL, Lindbuchler DM, Flansburg CN, Leeming R, Vogel VG, Lebo MS, Mason-Suares H, Hoskinson DC, Abul-Husn NS, Dewey FE, Overton JD, Reid JG, et al.
The current state of clinical interpretation of sequence variants
Hoskinson DC, Dubuc AM, Mason-Suares H
The C terminus of Pcf11 forms a novel zinc-finger structure that plays an essential role in mRNA 3'-end processing
Yang F, Hsu P, Lee SD, Yang W, Hoskinson D, Xu W, Moore C, Varani G
DNA damage induces targeted, genome-wide variation of poly(A) sites in budding yeast
Graber JH, Nazeer FI, Yeh PC, Kuehner JN, Borikar S, Hoskinson D, Moore CL
Conference Presentations
Sharing insights and latest findings at leading scientific conferences.
Whole genome sequencing uncovers novel BCR::ABL1 breakpoints and variants in leukemia: Implications for personalized medicine
Robert Huether, Derick Hoskinson, Raul Torres, Karl Beutner, Yan Yang, Kelly Potts, Andrew Frazier, Adam Hockenberry, Brett Mahon, Charles Koyias, Cecile Rose Vibat, Victoria Chiou, Michael Thompson, Kate Sasser, Halla Nimeiri
Comprehensive Whole Genome Sequencing (WGS) Assay Provides Diagnostic Insight into Clinically Relevant Genomic Alterations Across Myeloid Malignancies
Robert Huether PhD, Derick Hoskinson, Pavana Anur, Raul Torres PhD, Karl R. Beutner, Kristiyana Kaneva, Yan Yang, Kelly A. Potts, Andrew Frazier, Iris Braunstein, Brett Mahon MD, Michael A. Thompson MD PhD, Kate Sasser, PhD, Halla Nimeiri, MD, Lewis J. Kraft, PhD, Francisco M. De La Vega, Guillermo Garcia-Manero, MD
Detection of KMT2A Partial Tandem Duplication (PTD) in AML by Whole Genome Sequencing (WGS): Addressing Limitations of Traditional Techniques in the Era of Revumenib Approval
Robert Huether, Derick Hoskinson, Pavana Anur, Raul Torres, Karl R. Beutner, Kristiyana Kaneva, Yan Yang, Kelly A. Potts, Andrew Frazier, Iris Braunstein, Brett Mahon, Michael A. Thompson, Kate Sasser, Halla Nimeiri, Lewis J. Kraft, Francisco M. De La Vega, Alejandro Marinos Velarde
Get In Touch
Whether you're interested in a collaboration, have a question about my work, or just want to connect, I'd love to hear from you.
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Investigation Log
Investigator
define evade
Arkham Intelligence
**Evade (Evade action)** is an action you can take during your turn (in the investigation phase) to try to escape an enemy that is **engaged with you**. To do so, you make an **[agility] test** against that enemy’s **evade value**. If you succeed, you have **evaded** the enemy; if you fail, the enemy stays engaged with you. **When an enemy is evaded (by an evade action or by a card effect):** - The enemy becomes **exhausted** (if it was ready), and - The enemy **disengages** from you (engagement is broken). Move it from your threat area to your location to show it is no longer engaged. Notes: - If something says it **“automatically” evades** an enemy, you **do not** make a skill test. - Unlike fight or engage, you can only take the basic **evade action** against an enemy **engaged with you**.
Investigator
define forced
Arkham Intelligence
In *Arkham Horror: The Card Game*, **Forced** refers to a **forced ability**. A **forced ability** is identified by the bold **“Forced –”** command, and it **automatically initiates at its specified timing point** (often indicated by words like **“when,” “after,” “if,”** or **“at”**). Key points: - If the forced ability **does not have the potential to change the game state**, it **does not initiate**. - If it **does** have the potential to change the game state, its initiation is **mandatory each time** its timing point is met. - **“Forced – When…”** abilities initiate **as soon as** the timing point is reached, **before** that timing point’s impact resolves; **“Forced – After…”** abilities initiate **immediately after** the timing point’s impact resolves.