ArticleNPJ systems biology and applications2024
Bridging silicon and carbon worlds with digital twins and on-chip systems in drug discovery.
Article in NPJ systems biology and applications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- PK-Informed Microphysiological Systems: From Dynamic Dosing to Quantitative In Vitro-In Vivo Translation.Pharmaceutics · 2026Review
- Artificial Intelligence-Driven Reproductive Bioengineering: Integrating Fertility Diagnostics, Organ-on-Chip Systems, Cryobiology and Epigenetic Safety for Precision Reproductive Medicine.Bioengineering (Basel, Switzerland) · 2026Review
- Precision oncology in the age of AI: lessons from AI-driven drug discovery and clinical translation.BJC reports · 2026Review
- Towards credible digital twins for basic and preclinical research.Nature reviews. Methods primers · 2026Article
- Digital Twin Pathology of Skin Cancer.Journal of cosmetic dermatology · 2025Article
- Enhancing randomized clinical trials with digital twins.NPJ systems biology and applications · 2025Review
- The Potential Use of Digital Twin Technology for Advancing CAR-T Cell Therapy.Current issues in molecular biology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
This perspective discusses the convergence of digital twin (DT) technology and on-the-chip systems as pivotal innovations in precision medicine, substantially advancing drug discovery. DT leverages extensive health data to create dynamic virtual patient models, enabling predictive insights and optimized treatment strategies. Concurrently, on-the-chip systems from the Carbon world replicate human biological processes on microfluidic platforms, providing detailed insights into disease mechanisms and pharmacological interactions. The convergence of these technologies promises to revolutionize drug development by enhancing therapeutic precision, accelerating discovery timelines, and reducing costs. Specifically, it assesses their role in drug development, from refining therapeutic precision to expediting discovery timelines and reducing the final price. Nevertheless, integrating these technologies faces challenges, including data collection and privacy concerns, technical intricacies, and clinical adoption barriers. This manuscript argues for interdisciplinary cooperation to navigate these challenges, positing DTs and on-the-chip technologies as foundational elements in personalized healthcare and drug discovery.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.