Human disease models in drug development

In the paper

“Non-human primates are often the only pharmacologically relevant species, whose use has ethical and economic implications7.”

What the sources say

• Partly supported

  The Discussion (page not specified) says that, for many monoclonal antibodies, non-human primates are the only pharmacologically relevant species. The Introduction calls for ethically justified use and reduced NHP use, but the passages do not address economic implications. (LLM, conf=0.86)

  cites [7] Brennan, F. R. et al. Safety testing of monoclonal antibodies in non-human primates: case studies highlighting their impact on human risk assessment. mAbs 10, 1–17 (2018). sourceExperimental — accuracy not yet measured

In the paper

“Promising disease models of the liver65,66, pancreas67,68, central nervous system35,69,70, skin71, lung72,73, intestine72–76, musculoskeletal system77 and heart78–81 have been developed, but their equivalence or superiority over their animal models needs to be demonstrated.”

What the sources say

• Supported

  The citation is attached to the liver-model example, not to the sentence’s later assessment of equivalence to animal models. The Results section (‘Development of the Liver-Chip for modeling ALD/ASH’) describes a human Liver-Chip built to model alcohol-associated liver disease. (LLM, conf=0.93)

  cites [65] Nawroth, J. C. et al. Modeling alcohol-associated liver disease in a human liver-chip. Cell Rep. 36, 109393 (2021). source
• Partly supported

  The Discussion describes a developed human pancreatic-islet–liver chip that models glucose regulation, supporting its citation as a promising pancreatic platform. But it says inducing type 2 diabetes conditions is a next step; the paper does not establish that this chip already models the disease. The source does not compare its performance with animal models. (LLM, conf=0.86)

  cites [67] Bauer, S. et al. Functional coupling of human pancreatic islets and liver spheroids on-a-chip: towards a novel human ex vivo type 2 diabetes model. Sci. Rep. 7, 14620 (2017). sourceExperimental — accuracy not yet measured
• Supported

  The Results section (‘Cerebral organoids model human microcephaly’) describes testing cerebral organoids as a model of a neurodevelopmental disorder. This supports citing the paper as an example of a central nervous system disease model; the other organ systems are covered by other citations in the sentence. (LLM, conf=0.92)

  cites [35] Lancaster, M. A. et al. Cerebral organoids model human brain development and microcephaly. Nature 501, 373–379 (2013). source

In the paper

“most animal models poorly resemble human conditions and thus have low predictive values.”

What the sources say

• Partly supported

  The Introduction says animal-study results often fail to predict human results and that animal disease models can have molecular and cellular mechanisms distinct from those in humans. It does not establish that most animal models poorly resemble human conditions; it notes that some may appear phenotypically similar. (LLM, conf=0.86)

  cites [6] Ingber, D. E. Human organs-on-chips for disease modelling, drug development and personalized medicine. Nat. Rev. Genet. 23, 467–491 (2022). sourceExperimental — accuracy not yet measured

In the paper

“OoCs are perfused microfluidic platforms that contain bioengineered or miniaturized tissues or organs interconnected by 3D microchannels to simulate the in vivo functions, biomechanics and (patho)physiological responses of organs6,52–54.”

What the sources say

• Partly supported

  The Introduction describes organ chips as microfluidic devices with living cells and tissues in channels under dynamic fluid flow, designed to model organ functions and disease states. But it says only some recreate mechanical cues, while the Microfluidic organ chips section includes single-channel devices; interconnected tissues and 3D channels are therefore not defining features of all organ chips. The supplied passages have no page numbers. (LLM, conf=0.84)

  cites [6] Ingber, D. E. Human organs-on-chips for disease modelling, drug development and personalized medicine. Nat. Rev. Genet. 23, 467–491 (2022). sourceExperimental — accuracy not yet measured
• ?Could not verify

  The passages available from our copy are bibliographic metadata, not a description of how organs-on-chips are constructed or what they simulate. Searches for microfluidic devices, 3D microchannels, biomechanics, and pathophysiological responses found no passage addressing the claim. (LLM, conf=0.74)

  cites [52] Low, L. A., Mummery, C., Berridge, B. R., Austin, C. P. & Tagle, D. A. Organs-on-chips: into the next decade. Nat. Rev. Drug Discov. 20, 345–361 (2021). sourceExperimental — accuracy not yet measured
• Partly supported

  The Introduction describes organs-on-chips as engineered tissue constructs that reproduce selected organ functions using physical signals and fabricated channels. But it says these constructs are not mini-organs, and the section on combining single-organ models describes several ways to connect them—not necessarily 3D microchannels. The claim therefore overstates what all organs-on-chips contain. Page numbers are unavailable in our copy. (LLM, conf=0.88)

  cites [53] Vunjak-Novakovic, G., Ronaldson-Bouchard, K. & Radisic, M. Organs-on-a-chip models for biological research. Cell 184, 4597–4611 (2021). sourceExperimental — accuracy not yet measured

In the paper

“human-based models have so far been primarily used for toxicity testing61–64, and their application in preclinical and clinical research is still in its infancy.”

What the sources say

• Partly supported

  Section 5.5 describes chemical safety testing as a major driver of human-based alternative methods. Section 3.1 presents wider pharmaceutical adoption of microphysiological systems, including use during clinical development, as prospective. The paper does not establish that human-based models have been used primarily for toxicity testing or that preclinical and clinical research applications as a whole remain in their infancy; it also describes existing disease-modeling and drug-development applications. Page numbers were not available in our copy. (LLM, conf=0.82)

  cites [61] Marx, U. et al. Biology-inspired microphysiological system approaches to solve the prediction dilemma of substance testing. Altex 33, 272–321 (2016). sourceExperimental — accuracy not yet measured
• Partly supported

  The Introduction describes toxicity assays using human cells, and the Concluding Remarks discuss human organoids as potential tools for toxicity evaluation. Neither section establishes that human-based models have been used primarily for toxicity testing; the review also says reports of organoid toxicity studies remain very limited. It does not assess whether their preclinical or clinical use is still in its infancy. (LLM, conf=0.77)

  cites [62] Matsui, T. & Shinozawa, T. Human organoids for predictive toxicology research and drug development. Front. Genet. 12, 767621 (2021). sourceExperimental — accuracy not yet measured
• Supported

  The Introduction describes a strong shift in human stem-cell applications toward toxicology assessment, and §4 describes organoid use in toxicity screening. These passages support the toxicity-testing clause to which the citation is attached; the preclinical and clinical clause follows the citation. (LLM, conf=0.85)

  cites [63] Li, M. et al. Advanced human developmental toxicity and teratogenicity assessment using human organoid models. Ecotoxicol. Environ. Saf. 235, 113429 (2022). source

In the paper

“Biomedical research is undergoing a paradigm shift towards approaches centred on human disease models owing to the notoriously high failure rates of the current drug development process.”

• Also stated in: § Introduction · plain

  “Biomedical research is currently undergoing a paradigm shift towards approaches centred on human disease models1. This shift has been driven by the notoriously high failure rates of the current drug development process.”

What the sources say

• Partly supported

  The Abstract links poorly predictive animal models to high clinical-trial failure rates and says researchers are calling for a shift toward human-centred approaches. It does not establish that biomedical research is already undergoing that shift; the section on available preclinical models says the impact of human-based models remains low. (LLM, conf=0.87)

  cites [1] Adhikary, P. P., Ul Ain, Q., Hocke, A. C. & Hedtrich, S. COVID-19 highlights the model dilemma in biomedical research. Nat. Rev. Mater. 6, 374–376 (2021). sourceExperimental — accuracy not yet measured

In the paper

“Multipotent adult stem cells (ASCs) and induced pluripotent stem (iPS) cells can help overcome this shortage, as they can readily and indefinitely propagate and convert into any somatic cell10.”

What the sources say

• Partly supported

  The Introduction says primary patient cells are scarce because they proliferate poorly, and describes hiPSCs as having high proliferative capacity and the potential to yield multiple cell types. It does not extend those properties to adult stem cells or say that either cell type propagates indefinitely or can become any somatic cell type. No page numbers are provided in our copy. (LLM, conf=0.88)

  cites [10] Brooks, I. R. et al. Functional genomics and the future of iPSCs in disease modeling. Stem Cell Rep. 17, 1033–1047 (2022). sourceExperimental — accuracy not yet measured

In the paper

“biophysical processes, such as chip perfusion, can be easily automated using OoCs, which allows monitoring of tissue function and responses in situ and in real time52.”

What the sources say

• ?Could not verify

  The supplied passages contain bibliographic metadata, not discussion of organ-on-chip capabilities. Searches of our copy for automated chip perfusion and real-time, in situ monitoring of tissue function returned no substantive passage, so the claim cannot be assessed from the available text. (LLM, conf=0.70)

  cites [52] Low, L. A., Mummery, C., Berridge, B. R., Austin, C. P. & Tagle, D. A. Organs-on-chips: into the next decade. Nat. Rev. Drug Discov. 20, 345–361 (2021). sourceExperimental — accuracy not yet measured

In the paper

“The size of these organ-like structures ranges from 100 µm (lung organoid) to 2 mm (brain organoid) and they can be cultivated in small dimensions (for example, 96-well or 384-well plates25,26), thereby being suitable for high-throughput screening.”

What the sources say

• Supported

  The citation is attached to the claim about cultivation in 96- or 384-well plates, not the lung and brain size figures. The Introduction describes organoid testing in 96-well plates, and the Results demonstrate human colon organoid culture in 384-well plates with readouts suitable for high-throughput screening. (LLM, conf=0.91)

  cites [25] Du, Y. et al. Development of a miniaturized 3D organoid culture platform for ultra-high-throughput screening. J. Mol. Cell Biol. 12, 630–643 (2020). source
• Partly supported

  The Forskolin Induced Swelling (FIS) Assay methods describe seeding human colon organoids in 96-well plates, supporting the small-well part of the claim. They do not give the stated 100 µm lung-to-2 mm brain size range or describe cultivation in 384-well plates, and the protocol does not establish high-throughput screening across organoid types. (LLM, conf=0.86)

  cites [26] Vonk, A. M. et al. Protocol for application, standardization and validation of the forskolin-induced swelling assay in cystic fibrosis human colon organoids. STAR Protoc. 1, 100019 (2020). sourceExperimental — accuracy not yet measured

In the paper

“At the beginning of the pandemic, it was unclear which species were susceptible to SARS-CoV-2 and no model was readily available to study the course of the disease and identify druggable targets against the unknown pathogen9.”

What the sources say

• Partly supported

  The Abstract says the WHO convened experts in February 2020 to develop COVID-19 animal models, and the Conclusions describe efforts to determine which species are susceptible. These passages support the early uncertainty and need for models, but they do not establish that models were needed specifically to identify druggable targets. (LLM, conf=0.82)

  cites [9] Muñoz-Fontela, C. et al. Animal models for COVID-19. Nature 586, 509–515 (2020). sourceExperimental — accuracy not yet measured

In the paper

“cell responses and gene and/or protein expression patterns greatly differ between 2D and three-dimensional (3D) models11.”

What the sources say

• Supported

  The Background comparison table says gene and protein expression levels differ markedly between 2D cultures and in vivo-like 3D cultures. The Tumor Models and Immunotherapy section reports large gene-expression discrepancies between 2D and 3D cultures, while 3D Cell Culture for Drug Discovery reports different cellular responses to drugs. These passages support the citing sentence; page numbers are not provided in our copy. (LLM, conf=0.92)

  cites [11] Jensen, C. & Teng, Y. Is it time to start transitioning from 2D to 3D cell culture? Front. Mol. Biosci. 7, 33 (2020). source

In the paper

“single-cell RNA sequencing (scRNA-seq) of kidney organoids showed that SARS-CoV-2 directly infects kidney cells, triggering pro-fibrotic events and features of polycystic kidney disease, closely resembling renal processes observed in individuals who are critically ill with COVID-19 (refs. 89,90).”

What the sources say

• Partly supported

  The Results and discussion sections on kidney organoids report scRNA-seq evidence of infection and profibrotic signaling; the patient-tissue results also report infection and increased fibrosis in COVID-19 kidneys. Our copy does not report polycystic kidney disease features in the organoids or in critically ill patients, so that part of the claimed resemblance is unsupported (pages not provided). (LLM, conf=0.88)

  cites [89] Jansen, J. et al. SARS-CoV-2 infects the human kidney and drives fibrosis in kidney organoids. Cell Stem Cell 29, 217–231.e8 (2022). sourceExperimental — accuracy not yet measured
• Partly supported

  The Results section, ‘SARS-CoV-2 infects organoid proximal tubules with pathogenic effects,’ supports direct infection of kidney organoid cells. But the paper used pre-existing PKD2–/– cystic organoids to test infection; it does not show that infection caused polycystic kidney disease features. The Methods describe using previously available organoid scRNA-seq data, while the patient comparison in Results concerns urinary proteins and interferon-response signatures—not scRNA-seq evidence of pro-fibrotic changes resembling renal processes in critically ill patients. Page numbers were not available in our copy. (LLM, conf=0.90)

  cites [90] Helms, L. et al. Cross-validation of SARS-CoV-2 responses in kidney organoids and clinical populations. JCI Insight 6, e154882 (2021). sourceExperimental — accuracy not yet measured

In the paper

“cyclin-dependent kinase inhibitors 4 and 6 (CDK4/6) facilitate T cell activation, resulting in a higher number of tumour-infiltrating T cells in PDOs, cultivated over several days in a microfluidic 3D chip setup.”

What the sources say

• Partly supported

  The Results section reports that CDK4/6 inhibitors increased cytokines associated with T-cell responses in patient-derived tumor spheroids cultured in 3D microfluidic devices. The Introduction places the increase in tumor-infiltrating T cells in vivo, not in those spheroids. The cited paper therefore supports T-cell activation and the chip model, but not the claimed higher number of infiltrating T cells in that model. (LLM, conf=0.88)

  cites [129] Deng, J. et al. CDK4/6 inhibition augments antitumor immunity by enhancing T-cell activation. Cancer Discov. 8, 216–233 (2018). sourceExperimental — accuracy not yet measured

In the paper

“Almost 1,600 molecules were screened using targeted RNA sequencing, resulting in the identification of an inverse agonist of oestrogen-related receptor-α as the lead compound, which proved effective in correcting dysregulated CAVD-relevant genes in primary aortic valve endothelial cells from individuals with CAVD and in genetically modified mice.”

What the sources say

• Supported

  The Discussion reports targeted RNA-seq screening of nearly 1,600 small molecules and identifies XCT790 as the most effective network-correcting molecule. It calls XCT790 an ERRα inverse agonist and reports correction of dysregulated genes in primary valve endothelial cells from patients with CAVD. The in vivo results report correction of dysregulated genes in the genetically modified mouse model. (LLM, conf=0.94)

  cites [108] Theodoris, C. V. et al. Network-based screen in iPSC-derived cells reveals therapeutic candidate for heart valve disease. Science 371, eabd0724 (2021). source

In the paper

“amodiaquine (for example, NCT04532931, NCT04502342)51 and imatinib111 (for example, NCT04394416) have entered clinical trials.”

What the sources say

• Supported

  The Discussion states that human Phase 2 COVID-19 treatment trials using amodiaquine had recently begun in Africa. Citation 51 is attached to amodiaquine; the sentence cites a different source for imatinib, so imatinib is not assessed here. (LLM, conf=0.93)

  cites [51] Si, L. et al. A human-airway-on-a-chip for the rapid identification of candidate antiviral therapeutics and prophylactics. Nat. Biomed. Eng. 5, 815–829 (2021). source
• ?Could not verify

  The citation to this paper is attached to imatinib, not amodiaquine. The ‘Drugs block SARS-CoV-2 infection’ section reports imatinib experiments in organoids and Vero cells, but our copy does not say that imatinib entered a clinical trial or mention NCT04394416 (searched: clinical trials and the trial identifier). (LLM, conf=0.76)

  cites [111] Han, Y. et al. Identification of SARS-CoV-2 inhibitors using lung and colonic organoids. Nature 589, 270–275 (2021). sourceExperimental — accuracy not yet measured

In the paper

“SARS-CoV-2 tropism for neurons87 and cortical astrocytes88 or its preference for mature cell types and distinct neurotoxic effects were demonstrated in brain organoids.”

What the sources say

• Supported

  The Results section reports SARS-CoV-2 entry into neurons of brain organoids and more virus-positive cells in Day-60 than Day-15 organoids, suggesting a preference for relatively mature neuronal cells. It also reports altered Tau localization and increased neuronal cell death after exposure. The citing sentence attaches the cortical-astrocyte claim to a different citation (88), so that claim is not assessed against this paper. (LLM, conf=0.91)

  cites [87] Ramani, A. et al. SARS-CoV-2 targets neurons of 3D human brain organoids. EMBO J. 39, e106230 (2020). source
• Partly supported

  The Results section on gliogenic cortical organoids (page unavailable) reports robust infection of astrocytes in week-22 organoids, but only rare infection of neurons. The paper supports astrocyte tropism and greater infection at a later organoid stage; it does not establish a general preference for mature cell types. The neuron-tropism claim is attached to citation 87, not this source, and the supplied organoid results do not establish the claimed distinct neurotoxic effects. (LLM, conf=0.84)

  cites [88] Andrews, M. G. et al. Tropism of SARS-CoV-2 for human cortical astrocytes. Proc. Natl Acad. Sci. USA 119, e2122236119 (2022). sourceExperimental — accuracy not yet measured

In the paper

“transcriptomic profiling of infected kidney organoids aligned with the proteomic profile of the urine of individuals who were critically ill with COVID-19, further validating the findings of the model.”

What the sources say

• ?Could not verify

  The Results section reports RNA sequencing of infected kidney organoids and analysis of COVID-19 patient kidney tissue, but no passage reports comparing organoid transcriptomes with patients’ urine proteomes. Searches for “urine,” “proteomics,” and “urine proteome” found no such comparison in our copy, so the claimed alignment and resulting validation cannot be verified. (LLM, conf=0.74)

  cites [89] Jansen, J. et al. SARS-CoV-2 infects the human kidney and drives fibrosis in kidney organoids. Cell Stem Cell 29, 217–231.e8 (2022). sourceExperimental — accuracy not yet measured
• Supported

  The Results section ('COVID-19+ patient urine expresses signatures found in organoids') reports that urine proteins were analyzed in critically ill patients and that transcripts corresponding to 8 of 9 elevated urinary proteins also increased in infected kidney organoids. The Discussion says this shared signature supports the physiological relevance of the organoid findings. (LLM, conf=0.93)

  cites [90] Helms, L. et al. Cross-validation of SARS-CoV-2 responses in kidney organoids and clinical populations. JCI Insight 6, e154882 (2021). source

In the paper

“the antimalarial drugs chloroquine and hydroxychloroquine, which received controversial attention during the COVID-19 pandemic, proved non-effective in a human lung-on-chip disease model, similar to clinical findings51.”

What the sources say

• Supported

  The Results section ('Identification of approved drugs as SARS-CoV-2 entry inhibitors') reports that chloroquine and hydroxychloroquine had no effect on SARS-CoV-2 pseudovirus entry in human Airway Chips and notes that they also failed to show benefits in human clinical trials. The Discussion likewise says the chips predicted their lack of efficacy in human patients. The on-chip result concerns viral entry under the tested conditions, rather than every possible measure of drug efficacy. (LLM, conf=0.94)

  cites [51] Si, L. et al. A human-airway-on-a-chip for the rapid identification of candidate antiviral therapeutics and prophylactics. Nat. Biomed. Eng. 5, 815–829 (2021). source

In the paper

“Organoids demonstrated the induction of inefficient interferon responses in SARS-CoV-2 infections84,85, revealing similar interferon signatures between SARS-CoV-2-infected bioengineered lung models and native human lungs”

What the sources say

• Partly supported

  The Results sections on IFN pathways and transcriptome-wide similarities report that infected alveolospheres activated interferon pathways and had strikingly similar IFN signatures to AT2 cells from COVID-19 patient lungs (page unavailable). The paper does not characterize the organoids’ interferon response as weak or inefficient; it reports significant upregulation of IFN-related transcripts, with inflammatory responses emerging at later times. (LLM, conf=0.85)

  cites [84] Katsura, H. et al. Human lung stem cell-based alveolospheres provide insights into SARS-CoV-2-mediated interferon responses and pneumocyte dysfunction. Cell Stem Cell 27, 890–904.e8 (2020). sourceExperimental — accuracy not yet measured
• Partly supported

  The Host responses section reports that SARS-CoV-2 infection induced a broad type I/III interferon-stimulated gene signature in the organoid-derived cultures. It does not characterize that response as weak or inefficient. The section compares the induction with a report on human bronchial epithelial cells, not with interferon signatures in native human lungs; no page number is available in our copy. (LLM, conf=0.84)

  cites [85] Lamers, M. M. et al. An organoid-derived bronchioalveolar model for SARS-CoV-2 infection of human alveolar type II-like cells. EMBO J. 40, e105912 (2021). sourceExperimental — accuracy not yet measured

In the paper

“Treatment with the antibody TNT005, a specific complement component 1s inhibitor, inhibited the immune reaction and rescued the functional deficits, prompting the FDA to approve clinical trials (NCT04658472).”

What the sources say

• Partly supported

  The Results (page unavailable) report that TNT005 inhibited patient-serum-mediated complement deposition and rescued motoneuron functional deficits in the CIDP and MMN chip models. The Abstract says the efficacy data were included in an investigational new drug application, and the Introduction links the model to clinical testing (NCT04658472). Neither passage says the FDA approved trials because of these findings. (LLM, conf=0.87)

  cites [116] Rumsey, J. W. et al. Classical complement pathway inhibition in a “human-on-a-chip” model of autoimmune demyelinating neuropathies. Adv. Ther. 5, 2200030 (2022). sourceExperimental — accuracy not yet measured

In the paper

“This endothelial dysfunction is exacerbated after the introduction of peripheral blood mononuclear cells, resulting in excessive inflammation82.”

What the sources say

• Supported

  The Discussion states that circulating PBMCs containing monocytes further exacerbated inflammatory responses and injury to endothelial barrier function in the SARS-CoV-2 infection model. This supports the citing sentence in that experimental context. (LLM, conf=0.94)

  cites [82] Lu, R. X. Z. et al. Vasculature-on-a-chip platform with innate immunity enables identification of angiopoietin-1 derived peptide as a therapeutic for SARS-CoV-2 induced inflammation. Lab Chip 22, 1171–1186 (2022). source

In the paper

“Although some OoC models have been maintained for up to 3 months55, the effective lifetime of most disease models spans over a few days”

What the sources say

• Partly supported

  The citation follows the three-month claim. The Abstract and Introduction report that this four-organ-chip maintained functional co-cultures for at least 28 days, supporting long-term maintenance but not the stated three-month duration. The later claim about most disease models is not attached to this citation. (LLM, conf=0.86)

  cites [55] Maschmeyer, I. et al. A four-organ-chip for interconnected long-term co-culture of human intestine, liver, skin and kidney equivalents. Lab Chip 15, 2688–2699 (2015). sourceExperimental — accuracy not yet measured

In the paper

“the similarity scaling approach140 adapts engineering techniques of dimensional analysis and similitude to OoCs. This strategy accounts for different similarity criteria (Box 1) simultaneously in a systematic framework”

What the sources say

• Supported

  The opening section (p. 1) explicitly proposes a framework for OoCs adapted from dimensional analysis and similarity in engineering. The Similarity criteria section (p. 2) applies several criteria to OoCs, while Case studies (p. 2) says the approach accounts for parameters and their interactions systematically. (LLM, conf=0.93)

  cites [140] Feng, J. J. & Hedtrich, S. A similarity scaling approach for organ-on-chip devices. Lab Chip 22, 3663–3667 (2022). source

In the paper

“microfabricated array devices using organoids at passage 0 provide drug screening results within a week without compromising the predictivity of patient responses to anticancer drugs152”

What the sources say

• Supported

  The Introduction says the microwell chip used passage-0 lung cancer organoids to test clinically recommended drugs within a week, without prolonged expansion. The Results report that the one-week on-chip tests agreed with evaluable patient responses, supporting the claim that the faster test retained predictive value. (LLM, conf=0.92)

  cites [152] Hu, Y. et al. Lung cancer organoids analyzed on microwell arrays predict drug responses of patients within a week. Nat. Commun. 12, 2581 (2021). source

In the paper

“Mass spectrometry-based proteomics measures protein abundance and dynamics, identifies subcellular protein localization and post-transcriptional modifications, and facilitates the generation of interaction networks162”

What the sources say

• Partly supported

  The Methods (Liquid chromatography mass spectrometry proteomics analysis; page unavailable) describe mass-spectrometry-based protein identification, and the Results (Differentiation of human small intestinal organoids; page unavailable) report protein abundance ratios. The Results (Temporal protein profiles; page unavailable) also track changes over time. Our copy does not show this approach identifying subcellular protein localization or post-transcriptional modifications, or generating protein interaction networks. (LLM, conf=0.88)

  cites [162] Kip, A. M. et al. Proteomics analysis of human intestinal organoids during hypoxia and reoxygenation as a model to study ischemia-reperfusion injury. Cell Death Dis. 12, 95 (2021). sourceExperimental — accuracy not yet measured

In the paper

“the medium circulation rate is disproportionately slow compared to physiological blood flow, which in turn slows down the transport of nutrients and metabolic processes in tissue models138”

What the sources say

• Partly supported

  In “Scaling methods” (page not provided), the paper describes one liver–skin model whose medium recirculated more slowly than blood in the human body: 15 minutes versus about 5 minutes. In “Considerations for designing MPSs” (page not provided), it says perfusion affects nutrient supply and could alter biochemical reaction kinetics, but it does not establish that slow circulation generally slows nutrient transport and metabolic processes across tissue models. (LLM, conf=0.86)

  cites [138] Sung, J. H., Wang, Y. & Shuler, M. L. Strategies for using mathematical modeling approaches to design and interpret multi-organ microphysiological systems (MPS). APL Bioeng. 3, 021501 (2019). sourceExperimental — accuracy not yet measured

In the paper

“it has proven difficult to balance competing key indices in multi-OoC setups; for a gut–liver system139, for example, a perfusion rate chosen for the gut to yield proper metabolic rates might result in drug exposure times in the liver that are too short”

What the sources say

• Partly supported

  Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  cites [139] Maass, C., Stokes, C. L., Griffith, L. G. & Cirit, M. Multi-functional scaling methodology for translational pharmacokinetic and pharmacodynamic applications using integrated microphysiological systems (MPS). Integr. Biol. 9, 290–302 (2017). sourceExperimental — accuracy not yet measured

In the paper

“CDK4/6 inhibition also showed high in vitro and in vivo activity and synergy with anti-PD-1 blocking antibodies129.”

What the sources say

• Supported

  The Results section reports that CDK4/6 inhibition combined with anti-PD-1 synergistically induced cell death in cultured tumor spheroids. It also reports that the combination outperformed either treatment alone in murine tumors, supporting the claimed activity and synergy. (LLM, conf=0.90)

  cites [129] Deng, J. et al. CDK4/6 inhibition augments antitumor immunity by enhancing T-cell activation. Cancer Discov. 8, 216–233 (2018). source

In the paper

“Notably, organoids can be cultivated over months and probably even years, thus enabling the investigation of tissue maturation in a disease context as shown for SARS-CoV-2 infections in brain organoids87”

What the sources say

• Partly supported

  The Results section reports that 60-day-old brain organoids showed signs of maturation and had more SARS-CoV-2-positive cells than 15-day-old organoids. This supports using organoids of different maturities to study infection, but the paper does not establish cultivation over years or investigation of tissue maturation during a prolonged infection; the Discussion says experiments with more mature organoids are still needed. Page numbers are unavailable in our copy. (LLM, conf=0.86)

  cites [87] Ramani, A. et al. SARS-CoV-2 targets neurons of 3D human brain organoids. EMBO J. 39, e106230 (2020). sourceExperimental — accuracy not yet measured

In the paper

“these models mainly focus on preclinical safety testing and not disease modelling and are not customizable169”

What the sources say

• Partly supported

  The Discussion (p. 7) says most commercial organ-on-chip platforms are tailored for pharmaceutical testing and only a few are suitable for disease modelling. The paper does not narrow that focus to preclinical safety testing: the Overview (p. 3) discusses both safety and efficacy. The opening summary (p. 1) says self-made systems offer opportunities for customized models, but does not establish that commercial systems cannot be customized. (LLM, conf=0.88)

  cites [169] Busek, M., Aizenshtadt, A., Amirola-Martinez, M., Delon, L. & Krauss, S. Academic user view: organ-on-a-chip technology. Biosensors 12, 126 (2022). sourceExperimental — accuracy not yet measured

In the paper

“broad clinical implementation of patient-specific disease models, such as PDOs, is currently hindered by low efficiencies in PDO establishment (60–70% success rate on average although, for some tissues, up to 90% have been reported for intestinal organoids151) as well as lengthy generation times and expansion procedures”

What the sources say

• Supported

  Split into 2 atoms — 2 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  cites [151] van de Wetering, M. et al. Prospective derivation of a living organoid biobank of colorectal cancer patients. Cell 161, 933–945 (2015). source

In the paper

“Spatial profiling provides further information on tissue organization and three-dimensional architecture, thereby being essential for model validation186,187”

What the sources say

• Partly supported

  The Results ('Spatial projection of organoid cell transcriptomes'; page not available) show that mapping organoid cells to a spatial brain atlas helps assess regional identity and can be visualized in three dimensions. The paper does not show that this profiling reveals the organoid tissue’s own three-dimensional architecture, or establish that it is essential for model validation. (LLM, conf=0.84)

  cites [186] Fleck, J. S. et al. Resolving organoid brain region identities by mapping single-cell genomic data to reference atlases. Cell Stem Cell 28, 1148–1159.e8 (2021). sourceExperimental — accuracy not yet measured
• Partly supported

  The paper’s main text (page unavailable in our copy) shows that Slide-seq resolves tissue organization and that co-registered hippocampal sections allow three-dimensional visualization. It does not say that spatial profiling is essential for model validation. (LLM, conf=0.85)

  cites [187] Rodriques, S. G. et al. Slide-seq: a scalable technology for measuring genome-wide expression at high spatial resolution. Science 363, 1463–1467 (2019). sourceExperimental — accuracy not yet measured

In the paper

“most models rely on the integration of only a few, pre-defined immune cell types, which, however, does not emulate the complexity of in vivo immunoregulation”

What the sources say

• Partly supported

  The Abstract (page not provided) says existing models fail to recreate an interface important for immune-cell transport. The Biomimetic Microsystems section (page not provided) acknowledges that this lung chip lacks alveolar macrophages. These passages support a limitation in modeling immune responses, but do not establish that most disease models integrate only a few pre-defined immune cell types. (LLM, conf=0.80)

  cites [143] Huh, D. et al. Reconstituting organ-level lung functions on a chip. Science 328, 1662–1668 (2010). sourceExperimental — accuracy not yet measured
• Partly supported

  The Introduction (page unavailable) says patient-derived intestinal organoids lack circulating immune cells and other features of the in vivo organ environment, supporting the concern that such models miss physiological complexity. It does not say that most disease models integrate only a few predefined immune cell types. (LLM, conf=0.78)

  cites [145] Bein, A. et al. Enteric coronavirus infection and treatment modeled with an immunocompetent human intestine-on-a-chip. Front. Pharmacol. 12, 718484 (2021). sourceExperimental — accuracy not yet measured
• Partly supported

  The Introduction says some earlier inflammatory-skin models used disease-associated cytokines but lacked actual immune cells, so they could not fully reflect complex skin–immune interactions. It does not establish that most disease models integrate a few pre-defined immune cell types; the examples it describes contain no immune cells. (LLM, conf=0.83)

  cites [154] Wallmeyer, L. et al. TSLP is a direct trigger for T cell migration in filaggrin-deficient skin equivalents. Sci. Rep. 7, 774 (2017). sourceExperimental — accuracy not yet measured
• Supported

  The Concluding remarks and perspectives section says most OOC devices capture only simplified immune components, such as macrophages or neutrophils, rather than the broader immune repertoire. The Immune organ-on-a-chip section adds that models using one or a few immune components provide limited information and calls for platforms that emulate more complex immune tissues. (LLM, conf=0.91)

  cites [155] Maharjan, S., Cecen, B. & Zhang, Y. S. 3D immunocompetent organ-on-a-chip models. Small Methods 4, 2000235 (2020). source
• Partly supported

  The Introduction says conventional 2D models lack the complexity needed to model immunotherapeutic effects and omit essential cellular factors. The Discussion says accurately modeling multifactorial immune-related toxicities would likely require resident immune cells and lymphoid structures. Neither passage establishes that most disease models integrate only a few pre-defined immune cell types. (LLM, conf=0.83)

  cites [156] Kerns, S. J. et al. Human immunocompetent Organ-on-Chip platforms allow safety profiling of tumor-targeted T-cell bispecific antibodies. eLife 10, e67106 (2021). sourceExperimental — accuracy not yet measured

In the paper

“‘living biobanks’ can provide access to patient-derived cells and organoids from large patient cohorts, and have already been established for different cancers124,151,176–178, genetic diseases such as cystic fibrosis, infectious diseases, chronic obstructive pulmonary disease and inflammatory bowel diseases179”

What the sources say

• Partly supported

  Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  cites [124] Lee, S. H. et al. Tumor evolution and drug response in patient-derived organoid models of bladder cancer. Cell 173, 515–528.e17 (2018). sourceExperimental — accuracy not yet measured
• Partly supported

  Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  cites [151] van de Wetering, M. et al. Prospective derivation of a living organoid biobank of colorectal cancer patients. Cell 161, 933–945 (2015). sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [176] Yan, H. H. N. et al. A comprehensive human gastric cancer organoid biobank captures tumor subtype heterogeneity and enables therapeutic screening. Cell Stem Cell 23, 882–897.e11 (2018). source
• ?Not checked — no full text of the sourcecites [177] Sachs, N. et al. A living biobank of breast cancer organoids captures disease heterogeneity. Cell 172, 373–386.e10 (2018). source
• Supported

  Split into 2 atoms — 2 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  cites [178] Jacob, F. et al. A patient-derived glioblastoma organoid model and biobank recapitulates inter- and intra-tumoral heterogeneity. Cell 180, 188–204.e22 (2020). source
• Partly supported

  Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  cites [179] Ramalho, A. S. et al. Correction of CFTR function in intestinal organoids to guide treatment of cystic fibrosis. Eur. Respir. J. 57, 1902426 (2021). sourceExperimental — accuracy not yet measured

In the paper

“ClinicalTrials.gov currently lists 131 studies for the search term ‘organoids’, most of which focus on cancer.”

In the paper

“they have limited cell diversity and lack self-renewal capacity in non-stem cell-based models.”

In the paper

“efforts are ongoing to develop bioengineered human-based (disease) models of high clinical biomimicry to close this translational gap.”

In the paper

“The discrepancies derive from different anatomical layouts and biological barriers, divergent receptor expression and immune responses, host specificities of microorganisms, and distinct pathomechanisms.”

In the paper

“these tissue models cannot be cryopreserved or propagated and therefore have a limited lifespan.”

In the paper

“ASC-derived organoids lack cells from the ectodermal and mesenchymal germ layer and are usually smaller than iPS cell-derived counterparts.”

In the paper

“Engineered cells, such as reporter cell lines, are also commonly used as they are amenable to high-throughput manufacturing and have high reproducibility and lower costs relative to stem cell-based methods.”

In the paper

“Primary cells are the preferred option owing to their higher genetic heterogeneity compared to cell lines, but their limited availability or in vitro proliferation capacity restricts their use.”

In the paper

“Currently, 40% of the drugs undergoing clinical trials are antibodies3.”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites [3] IQVIA Institute. Global Trends in R&D 2022 (IQVIA Institute, 2021).

In the paper

“Infection studies using human ASC-derived intestinal organoids provided the solution as they closely emulate the host environment by differentiating into physiologically active, multicellular epithelial tissues.”

What the sources say

• ?Not checked — no full text of the sourcecites [96] Ettayebi, K. et al. Replication of human noroviruses in stem cell-derived human enteroids. Science 353, 1387–1393 (2016). source

In the paper

“The efficacy of the lead compounds was assessed in iPS cell-derived motor neurons showing splice correction and restored protein levels.”

In the paper

“rectal organoids from 71 individuals with cystic fibrosis that harboured 28 different CFTR mutations revealed residual CFTR function and identified effective drug combinations.”

In the paper

“Risdiplam received its marketing authorization in the EU in 2021 and became the first orally available medication for spinal muscular atrophy.”

In the paper

“This system revealed that C. neoformans trespasses the blood–brain barrier through transcytosis, providing a potential therapeutic target to inhibit this process104.”

What the sources say

• ?Not checked — no full text of the sourcecites [104] Kim, J. et al. Fungal brain infection modelled in a human-neurovascular-unit-on-a-chip with a functional blood-brain barrier. Nat. Biomed. Eng. 5, 830–846 (2021). source

In the paper

“These findings relied entirely on human-derived cancer organoids and went from bench to bedside in just 3 years (NCT03526835)114.”

What the sources say

• ?Not checked — no full text of the sourcecites [114] Herpers, B. et al. Functional patient-derived organoid screenings identify MCLA-158 as a therapeutic EGFR × LGR5 bispecific antibody with efficacy in epithelial tumors. Nat. Cancer 3, 418–436 (2022). source

In the paper

“measuring the lumen area of the organoids allowed comparison of CFTR function among patients, thereby providing physicians with a reliable predicting tool for clinical decision-making.”

In the paper

“These results were replicated in clinical trials (for example, NCT04538664), eventually leading to the approval of amivantamab by the EMA for the treatment of non-small cell lung cancer.”

What the sources say

• ?Not checked — no full text of the sourcecites [115] Yun, J. et al. Antitumor activity of Amivantamab (JNJ-61186372), an EGFR-MET bispecific antibody, in diverse models of EGFR exon 20 insertion-driven NSCLC. Cancer Discov. 10, 1194–1209 (2020). source

In the paper

“infection studies in brain organoids showed that the Zika virus primarily infects neural progenitor cells, which increases neural cell death and reduces proliferation, thereby hampering neurogenesis and causing microcephaly99,100.”

What the sources say

• ?Not checked — no full text of the sourcecites [99] Qian, X. et al. Brain-region-specific organoids using mini-bioreactors for modeling ZIKV exposure. Cell 165, 1238–1254 (2016). source
• ?Not checked — no full text of the sourcecites [100] Garcez, P. P. et al. Zika virus impairs growth in human neurospheres and brain organoids. Science 352, 816–818 (2016). source

In the paper

“If the goal is to unravel disease mechanisms or study drug efficacy and safety, disease models with higher biomimicry and complexity are required”

In the paper

“Patient-specific disease models hold great potential for personalized and precision medicine”

In the paper

“The problem is further aggravated by variabilities in model composition, complexity and experimental protocols”

In the paper

“commercially available setups are often still very expensive and therefore not affordable for many laboratories”

In the paper

“single-cell proteomics is still in its infancy; measurements are time consuming, expensive and have a limited dynamic range of measurements, rendering it low throughput”

In the paper

“rigorous disease model validation is essential but often neglected”

In the paper

“Putative key components, such as cells or biomechanical cues relevant to the disease of interest, are included based on existing knowledge, yet the possibility to overlook and thus exclude disease-relevant contributors remains. This biased approach bears the risk of false-positive or false-negative results”

In the paper

“Human-based models from both sexes and different ethnicities could help pinpoint these inter-individual differences, thereby improving therapeutic assessment.”

In the paper

“Media mixtures are typically used in these models, which, however, could reverse tissue maturation because cells from different germ layers are exposed to unspecific factors. This mismatch could result in gene and protein expression levels that are atypical for the tissue of interest”

In the paper

“These two methods account for length and mass scales but not the time scale, and are often inaccurate”

In the paper

“Miniaturized models typically carry fewer cells and lack a pervasive vasculature to perfuse the tissue compared to actual organs”

In the paper

“Developing and maintaining bioengineered disease models require high-level expertise and costly infrastructures”

In the paper

“providing a universal disease model design is challenging because their usefulness is strongly context dependent and influenced by the intended use and relevant readout parameters”

In the paper

“when studying systemic conditions such as inflammation or metastatic cancer, complex multi-OoC setups are superior to single-tissue or organ models”

In the paper

“Similar to bulk RNA-seq, proteomic analysis at the bulk level provides a population average and obscures cellular heterogeneities”

In the paper

“Women are often underrepresented, partly owing to the risk of reproductive toxicity.”

In the paper

“2D high-throughput methods using patient-specific or genetically engineered cells are most suitable as they allow testing of a large number of compounds in a short time”

In the paper

“These combinatorial approaches could help identify effective drugs more reliably, although their actual impact has yet to be proven”

In the paper

“It is unrealistic to assume that the complexity of a human can be fully recapitulated in vitro”

In the paper

“personalized disease models are well suited for clinical decision-making and in clinical trials to diversify the patient cohorts with respect to ethnicity, sex or age”

In the paper

“Some OoC setups have the size of a coin (or even smaller), thereby making it difficult to cultivate actual 3D tissue models”

In the paper

“initial drawbacks, such as the lack of cell diversity, vascularization and the ability to study tissue crosstalk, have already been largely overcome”

In the paper

“animal models are still considered the gold standard and therefore are often requested by default by grant review panels or reviewers”

In the paper

“Animal testing is not going to be completely replaced in the near future for several reasons, one of them being that toxicity testing in animals is legally mandated before entering clinical trials”

In the paper

“different disease models are suitable for different applications; organoids, for example, are useful for high-throughput drug screenings, whereas OoCs are more applicable for drug safety and efficacy testing”

In the paper

“they are poorly suited for high-throughput screenings”