PURPOSE A postmarket evaluation of chemotherapy dosage forms in Ethiopia was conducted to test the accuracy of the chemoPAD, a paper analytical device for drug quality screening. MATERIALS AND METHODS In September of 2018 in Addis Ababa, Ethiopia, 41 anticancer drug dosage forms (representing 4 active ingredients, 5 brands, and 7 lot numbers) were collected and were rapidly screened for quality using a chemotherapy paper analytical device (chemoPAD). Confirmatory analysis via high performance liquid chromatography was conducted. RESULTS The chemoPAD showed that the correct active pharmaceutical ingredient was present in doxorubicin, methotrexate, and oxaliplatin injectable dosage forms. However, 11 of 20 cisplatin samples failed the screening test. Confirmatory assay by high-performance liquid chromatography showed that all 20 cisplatin samples—comprising three lot numbers of a product stated to be Cisteen—were substandard, containing on average 54% ± 6% of the stated cisplatin content. Inductively coupled plasma optical emission spectroscopy analysis of five representative samples found 57% to 71% of the platinum that should have been present. The sensitivity of the chemoPAD for detection of falsified products could not be measured (as none were present in these samples), but the selectivity was 100% (no false positives). The sensitivity for detection of substandard products was 55%, and the selectivity was 100% (no false positives). CONCLUSION Although instrumental analysis by pharmacopeia methods must remain the gold standard for assessing overall drug quality, these methods are time consuming and patients could be exposed to a bad-quality drug while clinical workers wait for testing to be performed. The chemoPAD technology could allow clinicians to check at the point of use for serious problems in the quality of chemotherapy drugs on a weekly or monthly schedule.
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Securing the Chain of Custody and Integrity of Data in a Global North-South Partnership to Monitor the Quality of Essential Medicines
Substandard and falsified (SF) pharmaceuticals account for an estimated 10% of the pharmaceutical supply chain in low- and middle-income countries (LMICs), where a lack of regulatory and laboratory resources limits the ability to conduct effective post-market surveillance and allows SF products to penetrate the supply chain. The Distributed Pharmaceutical Analysis Laboratory (DPAL) was established in 2014 to expand testing of pharmaceutical dosage forms sourced from LMICs; DPAL is an alliance of academic institutions throughout the United States and abroad that provides high quality, validated chemical analysis of pharmaceutical dosage forms sourced from partners in LMICs. Results from analysis are reported to relevant regulatory agencies and are used to inform purchasing decisions made by in-country stakeholders. As the DPAL program has expanded to testing more than 1000 pharmaceutical dosage forms annually, challenges have surfaced regarding data management and sample tracking. Here, we describe a pilot project between DPAL and ARTiFACTs that applies blockchain to organize and manage key data generated during the DPAL workflow, including a sample’s progress through the workflow, its physical location, provenance of metadata, and lab reputability. Recording time and date stamps with this data will create a permanent and verifiable chain-of-custody for samples. This secure, distributed ledger will be linked to an easy-to-use dashboard, allowing stakeholders to view results and experimental details for each sample in real time and verify the integrity of DPAL analysis data. Introducing this blockchain-based system as a pilot will allow us to test the technology with real users analyzing real samples. Feedback from users will be recorded and necessary adjustments will be made to the system before the implementation of blockchain across all DPAL sites. Anticipated benefits of implementing blockchain for managing DPAL data include efficient management for routing work, increasing throughput, creating a chain of custody for samples and their data in alignment with the distributed nature of DPAL, and using the analysis results to detect patterns of quality within and across brands of products and develop enhanced sampling techniques and best practices.
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- Award ID(s):
- 1842369
- NSF-PAR ID:
- 10356202
- Date Published:
- Journal Name:
- Blockchain in Healthcare Today
- ISSN:
- 2573-8240
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.30953/bhty.v5.230
