Draft for Monazza's review. Not published.
Monazza Shahab, PhD

Pharmacology · Toxicology · Omics data · Machine learning

Monazza Shahab, PhD

Independent Scientific Consultant, Pharmacology, Toxicology and Omics Data

I review nonclinical pharmacology and toxicology data, check scientific documents for accuracy, and reanalyze proteomics and transcriptomics datasets in R and Python. My background is bench research since 2018 at Wayne State, Memorial Sloan Kettering and the University of Michigan, six peer-reviewed papers on drug-induced ototoxicity, and invited peer review for Nature Portfolio journals.

Book a 20-minute intro call See the publication record

Research mentoring for students: STEM Bridge ↗

  • PhD, Pharmacology, Wayne State University
  • Certificate, Applied Machine Learning, Columbia University (Emeritus)
  • Formerly Memorial Sloan Kettering Cancer Center
  • Formerly University of Michigan

Mouse brain: Allen Mouse Brain Common Coordinate Framework v3, Allen Institute. Wang et al., Cell 2020.
Portrait of Monazza Shahab, PhD

At a glance

  • Six peer-reviewed papers, four as first author (PubMed, 2019 to 2025)
  • Invited peer reviewer for three journals (2025 to 2026)
  • Doctoral data that supported NIH R01 DC020299 (NIDCD)

Expertise

Areas of expertise

Six disciplines, one working method: check every conclusion against the data behind it.

  • Pharmacology

    Dose-response, EC50/IC50 and mechanism-of-action evidence.

  • Toxicology

    Drug-induced toxicity in cell line, zebrafish and mouse models.

  • Proteomics

    TMT LC-MS/MS quantitative proteomics and phosphoproteomics.

  • Transcriptomics

    RNA-seq, microarray and GEO meta-analysis in limma.

  • Machine learning

    Nested validation and permutation testing in Python.

  • Scientific QC

    Numbers against source data, claims against citations.

Consulting engagements

What I help with

Four kinds of engagement, each one tied to work already on my record. Every engagement is scoped to one dataset, document or question.

Nonclinical pharmacology and toxicology data review

An independent read of research-stage in vitro and in vivo work: study design, dose-response and EC50/IC50 data, mechanism-of-action evidence, and the figures and tables built from them. I check that each conclusion follows from the data and flag the gaps.

On the record: drug-induced toxicity studies in cell lines, zebrafish and mouse models at Wayne State (2018 to 2022); dose-response studies of the gamma-secretase inhibitor nirogacestat in patient-derived desmoid tumor cell lines at Memorial Sloan Kettering (2023 to 2024).

Scientific document QC and writing support

An accuracy and consistency review of manuscripts, grant sections, study reports and responses to reviewers. Numbers are checked against source data, methods against results, and claims against citations. I also edit and draft manuscripts and NIH-style grant sections.

On the record: invited reviewer for Communications Biology, Scientific Reports and Frontiers in Pharmacology; contributed to drafting NIH R01 DC020299 and its responses to reviewer comments; four first-author papers; member, American Medical Writers Association.

Proteomics and transcriptomics reanalysis in R, Python and machine learning

Reanalysis of TMT LC-MS/MS proteomics, RNA-seq and microarray data. That covers quality control, differential abundance with false discovery rate control, pathway and network analysis (GSEA, DAVID, STRING), and classification with nested validation and permutation testing. You get reproducible code and a written report.

On the record: Certificate, Applied Machine Learning, Columbia University (Emeritus), completed January 2026; the 5,225-protein cochlear study; a public nested machine learning reanalysis with open code; a three-dataset GEO meta-analysis.

AI evaluation of life-science content

An expert review of AI-generated pharmacology and toxicology content against peer-reviewed literature and source data. I also write and validate expert-level evaluation exercises built from wet-lab and pharmacology data.

On the record: AI Model Evaluation Specialist, Life Sciences (contract) since August 2026.

Have a dataset, a document or a study that needs a second set of expert eyes? Send a short description and the decision it feeds.

Book a 20-minute intro call

How an engagement works

Three steps, one question at a time

Every engagement starts small and stays scoped to the decision your material has to support.

  1. Step 1

    Intro call

    Book a 20-minute call or send a short email: what the material is, the question it has to answer, and your timeline.

  2. Step 2

    Scope and terms

    We scope the work to one dataset, document or question, and agree on terms before any files change hands.

  3. Step 3

    Review and report

    You get a written report. Reanalysis work also comes with reproducible code.

Selected results

Work, in numbers

Each figure below comes from the cited paper or preprint.

5,225
proteins identified

Cochlear synaptosome proteomics after cisplatin

TMTpro LC-MS/MS profiling of mouse cochlear synaptosomes identified 5,225 proteins. After Benjamini-Hochberg correction (5% false discovery rate), 351 changed in abundance with cisplatin: 249 up and 102 down. Co-treatment with the peroxynitrite scavenger MnTBAP attenuated the change in 27 proteins. It also prevented the cisplatin-induced loss of auditory brainstem response wave I amplitude.

Shahab et al., Hearing Research 2024 · doi:10.1016/j.heares.2024.109022

249 up102 down4,874 not called changed

One square per protein, all 5,225 identified. Colored squares changed in abundance with cisplatin at a 5% false discovery rate. Shahab et al., Hearing Research 2024.
4,667
quantified proteins reanalyzed

A nested machine learning reanalysis of that dataset Preprint

The tandem mass tag 16-plex data were reanalyzed from raw reporter ion abundances. The pipeline used channel-level quality control, empirical Bayes statistics, nested leave-one-out classification with exact permutation tests, and six protein marker panels for tissue composition. The work showed that preparation composition was confounded with treatment: adjusting for composition cut the share of proteins called changed by cisplatin from 15.9% to 6.6%, against 5% expected by chance. The Python code that reproduces every number is public.

Shahab, Research Square 2026 · doi:10.21203/rs.3.rs-11340135/v1 · code on GitHub

Share of proteins called changed by cisplatin: 15.9% not adjusted for composition, 6.6% adjusted for composition, against 5% expected by chance. Not adjusted for composition 15.9% Adjusted for composition 6.6% 5% expected by chance
Percent of proteins called changed by cisplatin. Shahab, Research Square 2026.
7,311
differentially expressed genes across 3 GEO datasets

Cross-platform transcriptomic meta-analysis Preprint

Three public GEO datasets (skeletal muscle, whole blood, circulating neutrophils) were analyzed across four exercise contrasts in limma. At the discovery threshold, the analysis found 7,311 unique differentially expressed genes. No glutamatergic or neuroinflammatory term reached significance, and skeletal muscle and blood showed no concordance (r = 0).

Shahab and Balajee, bioRxiv 2026 · doi:10.64898/2026.10.27.762209

3
model systems, one mechanism

Nitrative stress and LMO4 in cisplatin ototoxicity

Linked cisplatin-induced protein nitration and loss of the transcriptional regulator LMO4 to hair cell death in organ of Corti cells, zebrafish neuromasts and a hair cell-specific Lmo4 conditional knockout mouse.

Experimental Cell Research 2019 · Toxicology and Applied Pharmacology 2021 · Molecular Neurobiology 2021

R01
NIH, NIDCD

Doctoral data behind an NIH R01

Her doctoral data supported NIH R01 DC020299, "Targeting nitrative stress for treatment of cisplatin ototoxicity" (Wayne State University; project period December 2022 to November 2027). She contributed to the proposal and to the responses to reviewer comments. Her 2024 and 2025 papers acknowledge the grant.

NIH RePORTER, 1R01DC020299-01A1 · PubMed grant records for PMID 38705005 and 40046635

Experience

Where the work was done

Bench toxicology, translational oncology and computational neuroscience, followed by independent scientific work.

  1. Aug 2026 to present

    AI Model Evaluation Specialist, Life Sciences (contract)

    Workada · Remote
    • Quality review of AI-generated pharmacology and toxicology content against peer-reviewed literature and source datasets.
    • Writes and validates expert-level scientific evaluation exercises from wet-lab and pharmacology data.
  2. Mar 2026 to present

    Research Mentor

    Inspira Advantage · Remote
    • Guides students through research design, scientific writing and manuscript preparation, with editorial and scientific review of drafts.
    • Trains undergraduate and post-baccalaureate researchers on computational biology pipelines and transcriptomic meta-analyses.
  3. Jul 2024 to Jul 2025

    Postdoctoral Researcher, Neuroscience and Computational Imaging

    University of Michigan, Department of Molecular and Integrative Physiology · Ann Arbor, MI
    • In vivo mouse studies under IACUC-approved protocols, including cranial window surgery and two-photon calcium imaging.
    • Co-developed a real-time Bayesian optimization system in MATLAB and Python. Co-author on the resulting conference posters at the Society for Neuroscience 2025 (lab announcement) and Cosyne 2026 (lab publications).
    • Lecturer, Winter 2025: PHY 610, Pathophysiology and Translational Physiology; PHY 415, Laboratory Techniques in Biomedical Research.
    Fluorescence micrograph of a sagittal section through the mouse superior colliculus: neurons and their fibers labeled red, cell nuclei stained blue with DAPI. Labeled Superior colliculus, with a 100 µm scale bar.
    From the Savier Lab, University of Michigan, where I worked as a postdoctoral researcher (2024 to 2025). Relota XJ, Ford A, Savier EL. J Neurosci 2025, Fig. 3B (cropped). CC BY 4.0.
  4. Mar 2023 to Jul 2024

    Research Scholar, Translational Oncology

    Memorial Sloan Kettering Cancer Center, Department of Surgery · New York, NY
    • Dose-response studies of nirogacestat in patient-derived desmoid tumor cell lines; established and characterized primary patient-derived cell lines from surgical specimens.
    • LC-MS/MS phosphoproteomics and RNA-seq/GSEA workflows; lentiviral shRNA knockdown for target validation.
    • Safety Representative: developed and enforced SOPs for biosafety, hazardous waste handling and laboratory compliance.
  5. May 2018 to Dec 2022

    Graduate Research Assistant, Auditory Neuroscience and Quantitative Proteomics

    Wayne State University, Department of Pharmacology · Detroit, MI
    • Mechanisms of cisplatin-induced ototoxicity in mouse models, zebrafish neuromast assays and organ of Corti cell cytotoxicity and apoptosis assays.
    • Built R pipelines for LC-MS/MS datasets with Benjamini-Hochberg false discovery rate correction.
  6. Aug 2015 to Aug 2017

    Graduate Teaching Assistant

    Wayne State University, Department of Biological Sciences · Detroit, MI
    • Ran introductory biology labs for about 120 undergraduates per semester across six semesters.

Publications

The publication record

Every entry links to its DOI. Peer-reviewed papers also link to PubMed. The full list is on ORCID 0000-0002-5134-2233, and all six papers come up in one PubMed author search for Monazza Shahab.

Peer reviewed Preprint, not peer reviewed First author Conference poster

Peer-reviewed articles 6 papers · 2019 to 2025

Preprints 2 · 2026 · not peer reviewed

Doctoral dissertation

Conference posters 2 · 2025 to 2026 · co-author

  1. 2026

    Preprint, not peer reviewed2026First author

    bioRxiv

    Peripheral exercise transcriptomes do not converge on glutamatergic or neuroinflammatory signatures: a cross-platform meta-analysis.

    Shahab M, Balajee A.

    Posted November 2, 2026.

    doi:10.64898/2026.10.27.762209
    Preprint, not peer reviewed2026Sole author

    Research Square

    Preparation composition confounds treatment effects in cochlear synaptosomal proteomics: a nested machine learning reanalysis of cisplatin and MnTBAP exposure.

    Shahab M.

    Posted October 20, 2026.

    doi:10.21203/rs.3.rs-11340135/v1Code on GitHub
    Conference poster2026

    Computational and Systems Neuroscience (Cosyne) 2026

    Real-Time Bayesian Optimization for Efficient Multidimensional Neural Tuning Characterization.

    Wu P, Shankar A, Chiu A, Shahab M, Burgess C, Savier E, Draelos A.

    Lab publications

  2. 2025

    Peer reviewed2025First author

    Toxicology Reports

    MnTBAP, a peroxynitrite scavenger, attenuates cisplatin-induced apoptosis and cytotoxicity in organ of Corti cells.

    Shahab M, Rosati R, Bhatia P, Doyon-Reale N, Jamesdaniel S.

    2025;14:101967.

    doi:10.1016/j.toxrep.2025.101967PubMed 40046635
    Conference poster2025

    Society for Neuroscience 2025, San Diego

    Real-time Bayesian Optimization System for Efficiently Characterizing Multidimensional Neural Responses.

    Wu P, Shankar A, Chiu A, Shahab M, Burgess C, Savier E, Draelos A.

    Lab announcement

  3. 2024

  4. 2023

    PhD dissertation2023

    Wayne State University, Department of Pharmacology

    Role of nitrative stress in cisplatin induced ototoxicity and synaptic dysfunction.

    Shahab M. Advisor: Samson Jamesdaniel, PhD.

    Wayne State Digital Commons

  5. 2022

  6. 2021

    Peer reviewed2021

    Molecular Neurobiology

    Lmo4 deficiency enhances susceptibility to cisplatin-induced cochlear apoptosis and hearing loss.

    Rosati R, Shahab M, Ramkumar V, Jamesdaniel S.

    2021;58(5):2019-2029.

    doi:10.1007/s12035-020-02226-4PubMed 33411315
    Peer reviewed2021First author

    Toxicology and Applied Pharmacology

    Cisplatin-induced hair cell loss in zebrafish neuromasts is accompanied by protein nitration and Lmo4 degradation.

    Shahab M, Rosati R, Meyer DN, Shields JN, Crofts E, Baker TR, Jamesdaniel S.

    2021;410:115342.

    doi:10.1016/j.taap.2020.115342PubMed 33245977

  7. 2019

    Peer reviewed2019

    Experimental Cell Research

    Inhibition of protein nitration prevents cisplatin-induced inactivation of STAT3 and promotes anti-apoptotic signaling in organ of Corti cells.

    Rosati R, Shahab M, Neumann WL, Jamesdaniel S.

    2019;381(1):105-111.

    doi:10.1016/j.yexcr.2019.05.008PubMed 31078568

Education and certificate

Training

  • Certificate, Applied Machine Learning, Columbia University (Emeritus)
    Completed January 2026. Underpins the machine learning side of the omics reanalysis engagements (service 03).
  • PhD, Pharmacology (minor: Physiology)
    Wayne State University School of Medicine, Detroit, MI, 2023. Dissertation on drug-induced neurotoxicity (cisplatin ototoxicity).
  • MS, Molecular Biotechnology
    Wayne State University, Detroit, MI, 2017
  • BTech, Biotechnology and Bioinformatics
    West Bengal University of Technology, Kolkata, 2014. Undergraduate research: built a partial genomic library of Bacillus subtilis and screened recombinants for amylase, protease and lipase activity (write-up, Biotech Articles, 2014, not peer reviewed).
  • Fellowships and awards
    Interdisciplinary Bioscience Fellowship, Wayne State University School of Medicine (2017 to 2019); Travel Award, Wayne State University School of Medicine (2020); Publication Award, Wayne State University (2022); Professional Development Award, University of Michigan (2025).

Peer review and service

Service

  • Invited peer reviewer
    Communications Biology, Nature Portfolio (2025, credited in the published article) · Scientific Reports, Nature Portfolio (2026, ORCID record) · Frontiers in Pharmacology (2026, credited in the published article)
  • Co-President, University of Michigan Postdoctoral Association
    Elected December 2024, served January to July 2025 · Official election results
  • Judge and abstract reviewer
    Graduate Research Symposium and Abstract Screening Committee, Wayne State University School of Medicine (2021 to 2022, 2025)
  • Graduate lecturer
    University of Michigan, Winter 2025: PHY 610 and PHY 415
  • Professional membership
    American Medical Writers Association (2024 to present)

FAQ

Frequently asked questions

Short, factual answers about my background, my work and how to reach me.

Who is Monazza Shahab?

Monazza Shahab, PhD, is a pharmacologist and independent scientific consultant in pharmacology, toxicology and omics data. She earned her PhD in Pharmacology at Wayne State University School of Medicine (2023) and holds a Certificate in Applied Machine Learning from Columbia University (Emeritus). She did research at Wayne State University, Memorial Sloan Kettering Cancer Center and the University of Michigan, and has published six peer-reviewed papers on cisplatin-induced ototoxicity. Her ORCID iD is 0000-0002-5134-2233.

What does Monazza Shahab consult on?

Four kinds of engagement: nonclinical pharmacology and toxicology data review; scientific document QC and writing support for manuscripts, grant sections, study reports and responses to reviewers; proteomics and transcriptomics reanalysis in R and Python, including machine learning with nested validation and permutation testing; and AI evaluation of life-science content against peer-reviewed literature and source data.

What has Monazza Shahab published?

Six peer-reviewed papers from 2019 to 2025, four as first author, in Toxicology Reports, Hearing Research, Pharmaceuticals, Molecular Neurobiology, Toxicology and Applied Pharmacology and Experimental Cell Research. She also has two 2026 preprints, on bioRxiv and Research Square (not peer reviewed), and a 2023 PhD dissertation at Wayne State University. The work covers cisplatin ototoxicity, nitrative stress, cochlear synaptosome proteomics and transcriptomic meta-analysis.

What methods and tools does she use?

TMT LC-MS/MS quantitative proteomics, LC-MS/MS phosphoproteomics, RNA-seq and microarray analysis, differential expression with limma and empirical Bayes statistics, Benjamini-Hochberg false discovery rate control, pathway and network analysis (GSEA, DAVID, STRING), and machine learning classification with nested leave-one-out validation and exact permutation tests, in R, Python and MATLAB. At the bench: cell line, zebrafish and mouse models of drug-induced toxicity, dose-response studies and two-photon calcium imaging.

How do I book a call with Monazza Shahab?

Book a 20-minute intro call in the booking section of monazzashahab.com, or email hello@monazzashahab.com with a short description of the material, the question it has to answer, and your timeline.

Work with me

Book a 20-minute intro call

A short call to talk through the material, the question it has to answer, and your timeline.

Set up a 20-minute intro call

Email me with a line about your project and two or three times that suit you, and I will send an invitation.

Email to book an intro call

Prefer email?

A useful first note covers:

  • what the material is (a dataset, a manuscript, a study package, a set of AI outputs);
  • the question it has to answer, or the decision it feeds;
  • your timeline.

Please do not send confidential data in a first email. We can agree on terms before any files change hands.