Cold Chain Digitalization in Regenerative Pharmacology: Ensuring Integrity, Traceability, and Quality of Biologics and Cell Therapies – A Narrative Review

2026

Толық мәтін Ашық қол жеткізу: Hybrid Метадеректер (CSL-JSON)
DOI 10.4103/wkrj.wkrj_29_26
Деректер сенімділігі 70 орташа
Бұл баға қалай есептеледі

Ол жазбаның өзінің тексерілетін белгілерінен құралады: мақаланың DOI-і бар ма, оның деректерін қанша тәуелсіз дереккөз растады, міндетті өрістер толтырылған ба және соңғы растау қаншалықты жаңа. Дереккөздер арасындағы алшақтық пен идентификатордың болмауы бағаны төмендетеді. 80-нен бастап мән жазбаның қосымша тексерусіз жарияланғанын, 60-тан 79-ға дейін — оның сенімділігі төмен күйде жарияланғанын және қолмен тексеру ұсынылатынын білдіреді. Редактор қолмен тексерген жазбаны қайта есептеу 90-нан төмен түсірмейді. Бұл — мақаланың өзіне емес, ол туралы деректерімізге берілген баға.

Аңдатпа

A BSTRACT Regenerative pharmacology increasingly relies on biologics and advanced therapy medicinal products (ATMPs) whose integrity and clinical utility depend on temperature-controlled logistics, robust traceability, and rapid, compliant decision-making across multi-stakeholder supply networks. Traditional cold chain practices often still paper-centric-struggle with interoperability, real-time risk detection, and patient-linked identity/custody requirements for cell and gene therapies. A narrative review was conducted using predefined search strings for PubMed, Scopus, and Web of Science (search date: 2026-04-14). Records were exported to a reference manager and screened in two stages (title/abstract, then full text when available). Inclusion criteria covered 2015–2026 publications, digital technologies applied to pharmaceutical/biopharmaceutical cold chains or directly transferable to ATMP logistics, and outcomes relevant to integrity, traceability, quality, risk management, or regulatory readiness. A thematic synthesis approach mapped evidence into technology domains (internet of things/sensors, artificial intelligence [AI]/machine learning, blockchain, digital twins (DTs), and cloud/data standards), and use-cases (biologics distribution and vein-to-vein ATMP workflows). The key regulatory context was triangulated from World Health Organization distribution guidance, European Union Good Distribution Practice, and US Current Good Tissue Practice (Title 21 of the Code of Federal Regulations, Part 1271). Seven publications met eligibility. DT analysis in biopharma identified cold chain complexity and paper-based monitoring as persistent constraints and highlighted sector-specific gaps in data interoperability, privacy/security, and return on investment (ROI)/validation tooling. Predictive stability modeling literature supports Bayesian and AI-enabled approaches to anticipate degradation, inform excursion decisions, and potentially accelerate access pathways. Big-data risk warning systems and emerging flexible sensing hardware expand real-time visibility in transport. Blockchain reviews and protocols emphasize chain-of-identity/custody and multi-party data sharing for decentralized ATMP manufacturing networks. Cold chain digitalization for regenerative therapeutics is best approached as an interoperable, validated socio-technical system rather than a single technology deployment. Near-term priorities are sensing, standardized data exchange, and risk-based quality governance; DTs and blockchain are promising but require clearer validation pathways, harmonized standards, and demonstrable ROI in regulated environments.