The study, led by Yuan Liu and Leng Han of the Indiana University School of Medicine together with colleagues including Eytan Ruppin, Douglas B. Johnson and Javid J. Moslehi, began with a sobering audit of the evidence base. Of the 487,688 trials listed on ClinicalTrials.gov up to March 2024, 97,254 were oncology-related and 7,274 involved immune checkpoint inhibitors. Yet only 210 of those immunotherapy trials — a mere 2.89 percent — included race information and enrolled more than 100 participants. The overwhelming majority, 86.77 percent, either lacked race information entirely or had enrolments too small to support meaningful comparisons. Most striking of all, among the 22 trials that enrolled at least 100 participants with more than 20 patients from each major racial group, not a single one reported adverse event data stratified by race.

To circumvent this data desert, the team turned to real-world evidence. They first mined Optum’s de-identified Clinformatics Data Mart Database, spanning 2007 to 2023 and encompassing 81.10 million insured individuals. Within it they identified 6.22 million patients with cancer diagnoses, of whom 91,852 received anti-PD-1 or anti-PD-L1 therapy: 1,979 Asian, 10,341 Black, 5,795 Hispanic and 65,907 white patients. Using diagnosis codes to capture immune-related adverse events arising after the start of checkpoint blockade, they documented 91,169 such events in 48,611 patients. After adjusting for age and sex with multivariable logistic regression, a clear pattern emerged: Black patients had higher odds of overall immune-related adverse events than Hispanic patients (odds ratio 1.08, 95 percent confidence interval 1.01 to 1.15), while Asian patients had lower odds than white patients (odds ratio 0.89, confidence interval 0.81 to 0.97).

Crucially, the findings did not rest on a single dataset. The team replicated the analysis in the National COVID Cohort Collaborative, a nationwide electronic health record resource containing data on 22.8 million individuals across 98 sites as of April 2024. The same directional patterns held: higher odds among Black patients compared with Hispanic patients, and lower odds among Asian patients compared with white patients. When the researchers stratified results by organ system using the MedDRA classification, aggregating adverse events into 13 system organ classes, they found that of 29 significant differences identified in the insurance database, 24 — 82.8 percent — showed consistent directional trends in the electronic health record cohort, a level of agreement that argues strongly against the results being statistical artifacts.

At the organ level, some of the differences were substantial. Black patients showed markedly higher odds of musculoskeletal and connective tissue disorders than Asian patients (odds ratio 1.44, confidence interval 1.30 to 1.60) and moderately higher odds than white patients (odds ratio 1.06). Conversely, Black patients had significantly lower odds of cardiac disorders than Asian patients (odds ratio 0.56, confidence interval 0.36 to 0.85), a finding with obvious clinical relevance given that checkpoint inhibitor myocarditis is among the most feared and fatal immune-related toxicities. When the analysis was further stratified by primary cancer site, the disparities sharpened: Black patients with stomach cancer had more than three times the odds of musculoskeletal disorders compared with Asian patients (odds ratio 3.31), white patients with liver cancer had lower odds of gastrointestinal disorders than Hispanic patients (odds ratio 0.68), and Black patients showed higher occurrence of nervous system disorders relative to Hispanic patients (odds ratio 1.42).

Drilling down to individual adverse event subtypes revealed even finer texture. Among 174 subtype-level comparisons tested in the insurance database, 60 showed differential odds across racial groups, and of the 56 that could be evaluated in the electronic health record cohort, 85.7 percent showed the same direction of effect. Arthritis stood out: Black patients had more than twice the odds of arthritis compared with Asian patients (odds ratio 2.27, confidence interval 1.92 to 2.68) and higher odds than white patients (odds ratio 1.27). Asian patients, by contrast, experienced significantly more rash than white patients (odds ratio 1.30), and in the validation cohort also showed higher rates of pruritus. In total, the researchers identified racial differences in 20 of the 29 immune-related adverse event types examined, indicating that the pattern is not confined to a handful of toxicities but pervades the entire spectrum of immunotherapy side effects.

Severity may differ as well. Because the real-world datasets do not natively record adverse event grades, the team used systemic steroid prescriptions as a proxy, following American Society of Clinical Oncology guidelines that recommend systemic steroids as first-line therapy for immune-related adverse events of at least grade 2. Among patients who experienced an adverse event, Black patients had the highest proportion of steroid exposure — 42.3 percent, compared with 39.9 percent for Hispanic and 39.2 percent for white patients — differences that reached statistical significance. The authors caution that drug claims do not specify why steroids were given, so the measure cannot pin severity to any particular toxicity, but it suggests that Black patients may shoulder a greater burden of serious, treatment-altering side effects.

The team also worked to rule out alternative explanations. A concern with any claims-based study is that differences in reporting or care patterns, rather than biology, might drive the results. To test this, they classified providers by patient composition and compared the average number of adverse events recorded per patient: providers predominantly serving white patients averaged 2.89 events per patient versus 2.88 for those predominantly serving non-white patients — no significant difference. Sensitivity analyses adjusting for comorbidities, neighborhood-level socioeconomic indicators and prior cancer treatments preserved the findings, with 89.1 percent of re-tested associations keeping the same direction of effect, a concordance significantly exceeding chance. Still, the authors are careful to note that the study is retrospective and observational, reflecting associations rather than proven causal relationships, and that residual confounding cannot be excluded.

Perhaps the most important caveat concerns what race actually represents. The authors emphasize that race is a social construct rather than a strictly biological variable, and that the observed disparities may reflect a tangle of influences: genetic variation in immune regulation, differences in tumor-immune interactions, unequal healthcare access, environmental exposures, surveillance intensity and the enduring effects of structural racism on diagnosis and treatment. They also note the limits of their data — the insurance database records race and ethnicity as a single combined variable, patients outside the four largest groups were too few to analyze, and the findings may apply most directly to patients covered by the insurer studied. Translating population-level patterns into individual clinical decisions, they warn, must be done cautiously to avoid entrenching the very disparities the work exposes.

What the study makes unmistakably clear is that the current system is flying blind. With 87.3 percent of checkpoint inhibitor trials on ClinicalTrials.gov conducted in the United States, where white patients dominate enrolment — even the landmark KEYNOTE-001 pembrolizumab trial, with 1,260 enrollees, counted only 63 Hispanic and 26 Black participants in total — safety signals in minority populations are systematically under-represented. Real-world datasets with millions of patients may be the only practical way to detect these differences. The authors call for racial diversity in both clinical trials and post-marketing surveillance, and for adverse events to be systematically recorded in a race-stratified manner. As immunotherapy reaches a growing share of the roughly 90,000 insured patients now treated annually, ensuring that its benefits and risks are understood — and managed — equitably across all populations has become not just a scientific imperative but a matter of basic fairness in cancer care.

Subject of Research: Racial disparities in immune-related adverse events during immune checkpoint inhibitor cancer therapy

Article Title: Disparities in adverse events during cancer immunotherapy

Article References: Liu, Y., Luo, M., Yang, J., Chen, Y., Zhang, P., Su, J., Huang, K., Salem, J.-E., Diao, L., Bian, J., Ruppin, E., Johnson, D. B., Moslehi, J. J., Han, L., on behalf of N3C, & Chute, C. G. (2026). Disparities in adverse events during cancer immunotherapy. Nature Health. https://doi.org/10.1038/s44360-026-00201-2

Image Credits: AI Generated

DOI: 10.1038/s44360-026-00201-2

Keywords: cancer immunotherapy, immune checkpoint inhibitors, immune-related adverse events, racial disparities, health equity, clinical trials, real-world data, PD-1 inhibitors, arthritis, pharmacovigilance, electronic health records, oncology

The technical foundation of the field rests on two reprogramming strategies. Integrative methods, which use retroviral or lentiviral vectors to deliver the classic quartet of factors—OCT4, SOX2, KLF4 and c-MYC—are efficient but insert themselves permanently into the genome, raising the specter of insertional mutagenesis and tumor formation. Non-integrative alternatives, including Sendai virus, episomal plasmids, synthetic mRNA and protein-based approaches, leave no genetic scars and are now favored for clinical translation, even though they tend to be less efficient and more expensive. The payoff is the ability to manufacture transgene-free, GMP-compliant cell lines suitable for personalized medicine and regenerative therapies, a goal that has come steadily closer over the review period.

What makes iPSCs so potent for drug discovery is their capacity to reproduce human disease in a dish. Patient-derived iPSCs can be coaxed into neurons, cardiomyocytes, hepatocytes or pancreatic beta cells that carry the exact genetic variants underlying a person’s illness, allowing researchers to study molecular mechanisms that animal models frequently misrepresent. This has proven particularly valuable for neurodegenerative disorders, cancer and metabolic conditions, where interspecies differences between mice and humans have derailed countless promising compounds. High-throughput screening campaigns can now run thousands of candidate drugs against disease-relevant human cells, identifying molecules that correct cellular pathologies rather than merely surviving toxicity filters designed around animal physiology.

The review highlights striking successes in drug repositioning, the rediscovery of new uses for existing medicines. Using patient-specific iPSC models, researchers identified statins as potential treatments for achondroplasia and the anticonvulsant ezogabine as a candidate therapy for amyotrophic lateral sclerosis. Screens against familial dysautonomia and ALS have similarly surfaced compounds that would have been difficult to find through conventional pipelines. These platforms are increasingly woven into clinical trials themselves, serving as pre-screening tools that predict how individual patients will respond to therapy, cutting down on trial-and-error prescribing and reducing adverse effects by matching the right drug to the right genetic background before the first dose is ever administered.

Nowhere is the approach more consequential than in Alzheimer’s disease, a condition that has devoured decades of research funding and an unbroken series of failed clinical trials. iPSC-derived neurons and glial cells now replicate the disease’s signature pathologies in vitro, including amyloid-beta accumulation and tau phosphorylation. High-content screens using these models flagged the anti-inflammatory drug cromolyn and antiparasitic avermectins as potential amyloid-lowering agents, while statins emerged as modifiers of phosphorylated tau. Tri-culture systems combining neurons, astrocytes and microglia have illuminated the glial dimension of neurodegeneration, and single-cell RNA sequencing has mapped gene expression changes across disease progression, surfacing new biomarkers. CRISPR/Cas9 editing of iPSC lines derived from patients with PSEN1 and PSEN2 mutations has allowed precise validation of therapeutic targets such as BACE1 and MAPT, and clarified unexpected links between cholesterol biosynthesis and amyloid precursor protein dysfunction.

Diabetes research has followed a parallel trajectory. Differentiation protocols guided by the transcription factors PDX1, NKX6.1 and Ngn3 now generate glucose-responsive, insulin-secreting beta-like cells from iPSCs, and recent studies have shown these cells can reverse hyperglycemia in streptozotocin-induced diabetic mice. Three-dimensional organoid systems have sharpened the maturity and glucose responsiveness of the derived cells, better approximating native pancreatic islets. Beyond replacement therapy, patient-derived iPSCs have been differentiated into endothelial cells that model diabetic vascular dysfunction, a screening platform that identified angiotensin receptor blockers as candidates for restoring endothelial function. Encapsulation of iPSC grafts in elastin-like recombinamers has shown promise for immunoprotection, addressing one of the central obstacles to durable cell replacement in type 1 diabetes.

In arthritis, the technology has produced some of the most inventive therapeutic engineering to date. CRISPR-engineered iPSC-derived macrophages have been designed to sense tumor necrosis factor-alpha and respond by autonomously secreting anti-inflammatory biologics such as soluble TNF receptor 1, quelling joint inflammation and bone erosion in murine models. iPSC-derived extracellular vesicles have reduced IL-1beta-driven chondrocyte death in osteoarthritis models while suppressing the cartilage-degrading enzymes ADAMTS5 and MMP13. Even more strikingly, vesicles from anti-inflammatory M2 macrophages can reprogram pro-inflammatory M1 macrophages within inflamed synovial tissue with efficiencies exceeding ninety percent, restoring a critical immune balance and boosting production of IL-10 and other tissue-protective cytokines. The iPSC secretome itself—exosomes, vesicles and growth factors—is emerging as a drug class in its own right, offering regenerative and immunomodulatory effects without the risks of transplanting live cells.

Cancer modeling has been equally transformed. Reprogramming tumor cells back to a pluripotent state can erase epigenetic damage, such as the hypermethylation of tumor suppressor genes in glioblastoma multiforme, creating a window into how malignancies originate. iPSC-based chimeras have modeled osteosarcoma and pancreatic ductal adenocarcinoma, while transient expression of the oncogene MLL-AF4 in iPSCs has reproduced B-acute lymphoblastic leukemia, and iPSCs carrying germline TP53 mutations have illuminated osteosarcoma formation in Li-Fraumeni syndrome. Organoids derived from iPSCs recreate the three-dimensional architecture of tumors, offering a far more faithful stand-in for the tumor microenvironment than flat cultures, and when combined with patient-derived xenografts they support biomarker discovery and pharmacological testing in vivo.

None of this has been easy. The review is candid about the field’s technical debts: genetic instability accumulates during reprogramming and long-term expansion, and even minor mutations introduced during cell generation can confer tumorigenic potential. Differentiation protocols vary between laboratories, producing inconsistent disease models and irreproducible drug response data. The costs of growth factors and specialized media under GLP and GMP standards are punishing, and residual undifferentiated cells raise unresolved immunogenicity concerns. Ethical questions compound the technical ones—donors are often inadequately informed about whether their cells may be used in human-animal chimera studies or germline-related research, incidental genetic findings are disclosed inconsistently, and regulatory oversight of cell therapies remains fragmented across jurisdictions, leaving openings for unproven treatments to reach vulnerable patients.

The authors’ prescriptions are pragmatic. They call for standardized differentiation protocols, shared reference cell lines and validation criteria to make results comparable across the field; deeper collaboration among academia, biotechnology and pharmaceutical companies and regulators to build scalable, compliant products; expanded investment in automation and machine learning to predict and control differentiation outcomes; transparent consent frameworks that spell out the full scope of possible research uses; long-term safety monitoring with centralized tracking of patients receiving iPSC-derived therapies; and sustained public engagement to build the trust on which the entire enterprise depends. If those foundations hold, the five years from 2020 to 2024 may be remembered as the period when drug development finally began to run on human biology rather than approximation—and the diseases that have resisted medicine longest may at last face models that truly resemble them.

Subject of Research: Applications of induced pluripotent stem cells in novel drug development from 2020 to 2024

Article Title: Recent progress in the use of induced pluripotent stem cells in novel drug development over the past 5 years (2020–2024)

Article References: Moseki, M. C., Makhzoum, A., Masisi, K., & Gaobotse, G. (2025). Recent progress in the use of induced pluripotent stem cells in novel drug development over the past 5 years (2020–2024). Discover Biotechnology, 2(1), Article 33. https://doi.org/10.1007/s44340-025-00042-x

Image Credits: AI Generated

DOI: 10.1007/s44340-025-00042-x

Keywords: induced pluripotent stem cells, iPSCs, drug discovery, disease modeling, Alzheimer's disease, diabetes, arthritis, cancer, personalized medicine, CRISPR, organoids, high-throughput screening