Pill characterization data streams for reducing exposure to inadequately identified anti-malarial medication in developing countries.

BACKGROUND: A large fraction of anti-malaria medicines (and indeed many other medicines classes) used in developing countries are inadequately identified. Framing this problem as one of misidentification rather than the more common framing of criminal misrepresentation leads to new solutions sets not currently being considered. METHOD: That reframing led to consideration and analysis of 4 new problems that informed design of a digital platform technology for delivering a distributed medicine characterization system: 1) problematic interests associated with a focus on preventing counterfeiting, 2) the complexity of the many ways that medicines can deviate from expected identities, 3) the challenge of choosing amongst a diversity of attribute characterization technologies, and 4) the need for a flexible and distributed data aggregation mechanism. RESULTS: Analysis of those new problems confirmed an initial insight that a previously described digital technology for tracking malaria tests results in infrastructure limited regions could be adapted for characterizing pill attributes. Feasibility is illustrated by describing how the platform design can be implemented using open-source software and commodity computational and communication technology readily available and supportable in developing countries. DISCUSSION: A system of this type would allow users to answer several questions. Is this medicine what it is supposed to be? Can it be used to treat locally encountered malaria? What has been the experience of others who have used pills having the same identity? Ubiquitous access to global digital telecommunication infrastructure allows the system to generate data streams from these distributed medicine characterization transactions that can be used to map global patterns of use of specifically identified medicines. This can provide feedback necessary to guide efforts to reduce the burden of malaria.

An informatics model for guiding assembly of telemicrobiology workstations for malaria collaborative diagnostics using commodity products and open-source software.

BACKGROUND: Deficits in clinical microbiology infrastructure exacerbate global infectious disease burdens. This paper examines how commodity computation, communication, and measurement products combined with open-source analysis and communication applications can be incorporated into laboratory medicine microbiology protocols. Those commodity components are all now sourceable globally. An informatics model is presented for guiding the use of low-cost commodity components and free software in the assembly of clinically useful and usable telemicrobiology workstations. METHODS: The model incorporates two general principles: 1) collaborative diagnostics, where free and open communication and networking applications are used to link distributed collaborators for reciprocal assistance in organizing and interpreting digital diagnostic data; and 2) commodity engineering, which leverages globally available consumer electronics and open-source informatics applications, to build generic open systems that measure needed information in ways substantially equivalent to more complex proprietary systems. Routine microscopic examination of Giemsa and fluorescently stained blood smears for diagnosing malaria is used as an example to validate the model. RESULTS: The model is used as a constraint-based guide for the design, assembly, and testing of a functioning, open, and commoditized telemicroscopy system that supports distributed acquisition, exploration, analysis, interpretation, and reporting of digital microscopy images of stained malarial blood smears while also supporting remote diagnostic tracking, quality assessment and diagnostic process development. CONCLUSION: The open telemicroscopy workstation design and use-process described here can address clinical microbiology infrastructure deficits in an economically sound and sustainable manner. It can boost capacity to deal with comprehensive measurement of disease and care outcomes in individuals and groups in a distributed and collaborative fashion. The workstation enables local control over the creation and use of diagnostic data, while allowing for remote collaborative support of diagnostic data interpretation and tracking. It can enable global pooling of malaria disease information and the development of open, participatory, and adaptable laboratory medicine practices. The informatic model highlights how the larger issue of access to generic commoditized measurement, information processing, and communication technology in both high- and low-income countries can enable diagnostic services that are much less expensive, but substantially equivalent to those currently in use in high-income countries.