Twenty years spent asking the same question — does this molecule change biology in a way that matters to a patient? — across every scale from a test tube to a clinical trial.
Before the publications, before the pharmaceutical companies, before the million-compound screens and the machine-learning platforms — there was a ten-year-old in Isfahan, Iran crouching over a microscope, watching pond water. Not because anyone told him to. Because what was in that water was, quite simply, impossible to believe.
Reza Beheshti Zavareh grew up in Isfahan — a city of extraordinary beauty, of ancient bridges and turquoise domes, of a culture that has always prized learning and inquiry — with the kind of curiosity that doesn't wait for school to catch up with it. His first microscope was a revelation in the most literal sense: a device that revealed an entire civilization invisible to the naked eye. Paramecia moving with apparent intention. Algae in geometries no human had designed. The developmental stages of goldfish — a creature he knew from a bowl on a shelf, now unfolding in front of him through a lens, transparent and extraordinary, all its future complexity packed into a cluster of dividing cells.
This was his first lesson in what science actually is: not the memorization of facts, but the experience of a world you didn't know existed until you looked more carefully. He wasn't yet thinking about drug discovery or molecular pharmacology or cancer biology. He was thinking about the pond. About what else was in it. About what the goldfish embryo would look like in three more hours.
Nature was his first teacher in a broader sense too. The animal kingdom, evolution, the branching logic of how life diversifies across millions of years — these were not abstract subjects in a textbook but a framework that made everything else make sense. The evolutionary instinct — to ask why a biological system is the way it is, not just what it is — would become the hallmark of his scientific thinking decades later in the drug discovery laboratory.
The University of Toronto's program in Genes, Genetics and Biotechnology gave Reza his first formal laboratory experiences — and they were not gentle introductions. One of the earliest and most formative was participation in LD50 determination studies: the systematic measurement of the dose of a compound lethal to fifty percent of a test population. It is a protocol that strips away sentimentality. A molecule is not good or bad; it has a dose-response relationship, a therapeutic window, a margin. Learning to think in those terms — rigorously quantitative, biologically grounded, clinically aware — shaped how he would approach pharmacology for the rest of his career.
In vivo testing followed. The experience of working with animal models early in one's training does something particular to a scientist: it imposes a moral weight that in vitro work does not. The question ceases to be whether the assay reads correctly and becomes whether the biology is real, whether the dose translates, whether the mechanism will survive contact with a whole organism. Reza internalized that weight rather than setting it aside — and it became the instinct that would later drive him to insist on disease-relevant cellular models and translational pharmacology endpoints throughout his career.
The most consequential undergraduate experience, however, was his involvement in a multiple myeloma clinical trial — a glimpse, at the very beginning of his scientific life, of where all the assays and the compounds and the animal models were ultimately supposed to lead. Multiple myeloma is a cancer of plasma cells, devastating and at the time largely incurable. Being part of a team working at the clinical interface — where the data was not fluorescence units in a plate reader but patient outcomes — left a mark that has never faded.
His Ph.D. thesis, "Investigation of the Role of the N-Glycosylation Pathway in Malignancy," emerged from a hypothesis that the field had underestimated. N-glycosylation — the attachment of complex sugar chains to proteins — had been characterized as a structural phenomenon, wallpaper on the surface of proteins. Reza's work helped reframe it as a functional regulator of cancer progression.
The papers that came from this period established the intellectual signature of his career: mechanistic precision combined with translational ambition. His 2008 Cancer Research publication demonstrated that inhibition of the sodium/potassium ATPase impairs N-glycan expression and function — a finding that linked a familiar ion transporter to an entirely unexpected biology. His 2012 PLoS One paper showed that suppression of N-glycan branching by GnTI knockdown inhibits cancer cell migration and metastasis.
Selected doctoral publications: Beheshti Zavareh R. et al., "Inhibition of the sodium/potassium ATPase impairs N-glycan expression and function." Cancer Research, 2008 · Beheshti Zavareh R. et al., "Suppression of N-glycan branching by GnTI knockdown inhibits cell migration and metastasis." PLoS One, 2012
Postdoctoral training at the California Institute for Biomedical Research (Calibr) and The Scripps Research Institute in La Jolla transformed Reza from a mechanistic cell biologist into something rarer: a scientist who can design experiments at the scale of a million compounds without losing the biological intuition that makes the data mean something.
At Calibr he designed assay cascades for both target-based and phenotypic lead discovery, applied high-content imaging and flow cytometry to compound profiling, and contributed to multiple high-impact programs. Among them: work on serine biosynthesis inhibitors published in PNAS (Mullarky et al., 2016), GOT1 enzyme inhibitors, and a landmark study on HSP90 inhibition and immune checkpoint modulation published in Cell Chemical Biology in 2020.
The HSP90 paper deserves special attention. Using a phenotype-based discovery approach, the team identified that small-molecule HSP90 inhibitors can directly decrease the expression of multiple immune checkpoint proteins — including PD-L1 and PD-L2 — at clinically relevant concentrations both in vitro and in vivo. In an era of intense interest in checkpoint blockade therapy, this was a finding with real translational stakes.
Joining Janssen Pharmaceutical Companies of Johnson & Johnson as a Scientist in Lead Discovery and Profiling marked Reza's transition from the academic-adjacent world of research institutes into the demanding operational reality of pharmaceutical drug discovery. Here, assays don't just need to work — they need to work reproducibly across hundreds of plates, transferred to CROs, scaled to automation, and defended to project teams who need answers on a Monday morning.
His signature contribution at Janssen was establishing and scaling high-throughput flow cytometry as a discovery platform — a methodological expansion that enabled hit identification, lead optimization, mechanism-of-action studies, and translational pharmacology across immunology, neuroscience, infectious disease, and virology. Building it into a true HTS platform required rethinking sample preparation, data acquisition, QC frameworks, and automation interfaces simultaneously.
His Janssen years also produced the NKG2D publication in PNAS (Thompson et al., 2023) — the identification of first-in-class small-molecule inhibitors for an NK cell receptor with significant implications for immune checkpoint biology and autoimmune disease.
As Associate Director at Trotana Therapeutics, Reza built a discovery biology function from the ground up — strategy, infrastructure, operating model, and the team itself. Managing four direct reports and executing multiple programs from target validation through candidate nomination, he operated at the intersection of scientific leadership and organizational architecture.
His current role as Principal Scientist at Montai Therapeutics places him at the frontier of what drug discovery is becoming. Montai's machine-learning-enabled platform integrates multimodal AI models with wet-lab biology to accelerate the design-make-test cycle beyond what any purely human team could achieve. Reza leads biological and molecular pharmacology strategy for immunology programs, defining assay cascades that must be robust enough to feed AI models with high-quality, minimally biased data — a fundamentally new scientific demand.
Across every institution in his career, a pattern recurs in Reza's colleagues' descriptions of him: they learned something. At Princess Margaret, at Calibr, at Janssen, at Trotana, at Montai — the lab notebooks fill with data, but so do the careers of the scientists who worked alongside him. Mentorship, in his view, is not a soft skill appended to the real work. It is the real work, scaled.
His approach to teaching science is direct: scientists should understand not just what a protocol says, but why every step exists, what it assumes, and under what conditions it fails. A junior scientist who understands why DMSO at 0.5% changes the assay window, why the plate map controls matter, and why a Z′-factor of 0.62 on a poorly designed assay is more dangerous than one of 0.45 on a well-designed one — that scientist becomes a force multiplier.
This site exists partly as an extension of that philosophy: a place where the reasoning behind the methods is written down, made searchable, and offered freely to the community of practitioners who are figuring it out right now.
While fully engaged at Montai Therapeutics, I take on a small number of consulting engagements each year where the scientific challenge is genuinely interesting and the fit is right. My focus is on early discovery problems that require both strategic thinking and deep experimental knowledge.
I'm reachable for scientific conversations, collaboration, consulting enquiries, peer review, and speaking invitations. I respond thoughtfully, though not always immediately.
Twenty years of hands-on platform building — from a Biomek FX in a Toronto hematology lab to designing a first-of-its-kind high-throughput flow cytometry system at Janssen, and now integrating experimental biology with machine learning at Montai.
Most scientists encounter automation as something that already exists when they arrive. Reza has repeatedly been the person who built it.
His first liquid handler was a Beckman Coulter Biomek FX — encountered in the University of Toronto's Department of Hematology. Learning a platform at that stage means internalizing something deeper than the protocol: how pipetting errors propagate, how dead volume behaves across tip types, how a CV of 3% in a 384-well plate means something entirely different from 3% in a 96-well plate.
At Calibr/Scripps, scale changed everything. The GNF Systems dispenser — purpose-built for 1536-well HTS — and the Labcyte Echo acoustic liquid handler together enabled compound dispensing at volumes previously impractical. The Agilent Bravo filled the gap for flexible cell-based workflows. At Janssen, the HighRes Biosolutions (HRB) modular robotic platform orchestrated multi-instrument integration — the backbone of the HT flow cytometry platform.
Training in the University of Toronto's Department of Hematology instills a particular discipline. Clinical flow cytometry demands panel reproducibility at a standard wet-lab research cytometry rarely meets.
Two decades of cytometry breadth — from analytical benchtop instruments to high-throughput screening cytometers — have produced genuine expertise in platform selection, panel design, compensation and unmixing strategy, QC frameworks, and the translation of cytometry readouts into pharmacological conclusions. The right cytometer for a given biology is a scientific decision, not a procurement one.
A defining early experience was working with a pre-commercial version of the IQue Screener (Intellicyt/Sartorius) before it had a commercial name or established workflows. Building HT cytometry methods from scratch — before field standards existed — became a recurring theme, culminating in the Janssen HT-FC platform design.
The instrument generates images. The science lives in deciding what to measure from them — a decision that cannot be undone after the experiment runs.
Experience spans the full arc of the field's development, from early ArrayScan campaigns at Calibr to confocal Opera Phenix workflows and morphological profiling with Cell Painting. The discipline is not operating the microscope; it's designing the assay before a single plate is imaged.
Cell Painting represents a philosophical shift in how imaging is used in drug discovery. Rather than asking "does compound X activate pathway Y?", it asks "what does compound X do to the cell — globally, without prior hypothesis?" Six-channel morphological profiling generates thousands of features per cell. Applied to mechanism-of-action studies, it reveals polypharmacology, toxicity signatures, and pathway engagement that target-focused assays miss entirely.
The plate reader is the workhorse of biochemical HTS. Knowing which reader to reach for — and which detection mode fits the assay biology — is the difference between a clean Z′ and a noise floor.
AI in biology is only as good as the experimental design that generated its training data. The scientist who built the platform is the one who can ensure the model has something real to learn from.
Engagement with AI/ML spans three distinct application layers, each requiring different expertise and each carrying specific failure modes when the underlying data is flawed.