Effects of extended transport on cryopreserved allogeneic hematopoietic progenitor cell (HPC) product quality and optimal methods to assess HPC stability.

BACKGROUND: Since the beginning of the COVID-19 pandemic, cryopreservation of hematopoietic progenitor cell (HPC) products has been increasingly used to ensure allogeneic donor graft availability prior to recipient conditioning for transplantation. However, in addition to variables such as graft transport duration and storage conditions, the cryopreservation process itself may adversely affect graft quality. Furthermore, the optimal methods to assess graft quality have not yet been determined. STUDY DESIGN AND METHODS: A retrospective review was performed on all cryopreserved HPCs processed and thawed at our facility from 2007 to 2020, including both those collected onsite and by the National Marrow Donor Program (NMDP). HPC viability studies were also performed on fresh products, retention vials, and corresponding final thawed products by staining for 7-AAD (flow cytometry), AO/PI (Cellometer), and trypan blue (manual microscopy). Comparisons were made using the Mann-Whitney test. RESULTS: For HPC products collected by apheresis (HPC(A)), pre-cryopreservation and post-thaw viabilities, as well as total nucleated cell recoveries were lower for products collected by the NMDP compared to those collected onsite. However, there were no differences seen in CD34+ cell recoveries. Greater variation in viability testing was observed using image-based assays compared to flow-based assays, and on cryo-thawed versus fresh samples. No significant differences were observed between viability measurements obtained on retention vials versus corresponding final thawed product bags. DISCUSSION: Our studies suggest extended transport may contribute to lower post-thaw viabilities, but without affecting CD34+ cell recoveries. To assess HPC viability prior to thaw, testing of retention vials offers predictive utility, particularly when automated analyzers are used.

Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review.

We followed a systematic approach based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses to identify existing clinical natural language processing (NLP) systems that generate structured information from unstructured free text. Seven literature databases were searched with a query combining the concepts of natural language processing and structured data capture. Two reviewers screened all records for relevance during two screening phases, and information about clinical NLP systems was collected from the final set of papers. A total of 7149 records (after removing duplicates) were retrieved and screened, and 86 were determined to fit the review criteria. These papers contained information about 71 different clinical NLP systems, which were then analyzed. The NLP systems address a wide variety of important clinical and research tasks. Certain tasks are well addressed by the existing systems, while others remain as open challenges that only a small number of systems attempt, such as extraction of temporal information or normalization of concepts to standard terminologies. This review has identified many NLP systems capable of processing clinical free text and generating structured output, and the information collected and evaluated here will be important for prioritizing development of new approaches for clinical NLP.

Application of Natural Language Processing and Network Analysis Techniques to Post-market Reports for the Evaluation of Dose-related Anti-Thymocyte Globulin Safety Patterns.

OBJECTIVE: To evaluate the feasibility of automated dose and adverse event information retrieval in supporting the identification of safety patterns. METHODS: We extracted all rabbit Anti-Thymocyte Globulin (rATG) reports submitted to the United States Food and Drug Administration Adverse Event Reporting System (FAERS) from the product's initial licensure in April 16, 1984 through February 8, 2016. We processed the narratives using the Medication Extraction (MedEx) and the Event-based Text-mining of Health Electronic Records (ETHER) systems and retrieved the appropriate medication, clinical, and temporal information. When necessary, the extracted information was manually curated. This process resulted in a high quality dataset that was analyzed with the Pattern-based and Advanced Network Analyzer for Clinical Evaluation and Assessment (PANACEA) to explore the association of rATG dosing with post-transplant lymphoproliferative disorder (PTLD). RESULTS: Although manual curation was necessary to improve the data quality, MedEx and ETHER supported the extraction of the appropriate information. We created a final dataset of 1,380 cases with complete information for rATG dosing and date of administration. Analysis in PANACEA found that PTLD was associated with cumulative doses of rATG >8 mg/kg, even in periods where most of the submissions to FAERS reported low doses of rATG. CONCLUSION: We demonstrated the feasibility of investigating a dose-related safety pattern for a particular product in FAERS using a set of automated tools.