Incorporating user needs into product development for improved infection detection for malaria elimination programs

Ebels, Kelly; Clerk, Christine; Crudder, Chris; McGray, Sarah; Magnuson, Kendall; Tietje, Kathy; LaBarre, Paul

doi:10.1109/ghtc.2014.6970338

Cited by 5 publications

(5 citation statements)

References 19 publications

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“…1. Forty-four TPPs were deemed eligible for inclusion in the systematic review [8][9][10]. Interreviewer agreement was high at title and abstract (κ = 96%) and full-text screening (κ = 98%).…”

Section: Literature Searchmentioning

confidence: 99%

“…This should, in turn, increase the likelihood that the test will be adopted into clinical practice and reimbursed [1]. A TPP should also account for contextual aspects that might affect the test's real-world performance [10], defining infrastructural and technical constraints that impact on the implementation into clinical practice. This review shows that TPPs to date have primarily been developed for global health applications, as the main funding organisations are WHO, UNICEF and Bill and Melinda Gates Foundation.…”

Section: Relevancy Of Tpps For Test Manufacturersmentioning

confidence: 99%

“…TPPs could therefore be particularly useful when designing 'fit for purpose' medical tests [10]; they could be used during the development and manufacturing phase to ensure that a new test meets pre-established operational and performance requirements, in line with unmet clinical need [7]. Generating the required evidence for a new test can take many years and significant investment [11].…”

Section: Introductionmentioning

confidence: 99%

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Target Product Profiles for medical tests: a systematic review of current methods

Cocco

Ayaz-Shah

Messenger

et al. 2020

BMC Med

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Background: A Target Product Profile (TPP) outlines the necessary characteristics of an innovative product to address an unmet clinical need. TPPs could be used to better guide manufacturers in the development of 'fit for purpose' tests, thus increasing the likelihood that novel tests will progress from bench to bedside. However, there is currently no guidance on how to produce a TPP specifically for medical tests. Methods: A systematic review was conducted to summarise the methods currently used to develop TPPs for medical tests, the sources used to inform these recommendations and the test characteristics for which targets are made. Database and website searches were conducted in November 2018. TPPs written in English for any medical test were included. Based on an existing framework, test characteristics were clustered into commonly recognised themes. Results: Forty-four TPPs were identified, all of which focused on diagnostic tests for infectious diseases. Three core decision-making phases for developing TPPs were identified: scoping, drafting and consensus-building. Consultations with experts and the literature mostly informed the scoping and drafting of TPPs. All TPPs provided information on unmet clinical need and desirable analytical performance, and the majority specified clinical validity characteristics. Few TPPs described specifications for clinical utility, and none included cost-effectiveness. Conclusions: We have identified a commonly used framework that could be beneficial for anyone interested in drafting a TPP for a medical test. Currently, key outcomes such as utility and cost-effectiveness are largely overlooked within TPPs though and we foresee this as an area for further improvement.

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Section: Literature Searchmentioning

confidence: 99%

Section: Relevancy Of Tpps For Test Manufacturersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Target Product Profiles for medical tests: a systematic review of current methods

Cocco

Ayaz-Shah

Messenger

et al. 2020

BMC Med

View full text Add to dashboard Cite

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“…Furthermore, few TPPs consider operational aspects such as deployment coverage in addition to product-specific characteristics such as efficacy or half-life. This has implications for the appropriate definition of intervention effectiveness characteristics according to local health systems and health targets ( 1, 6, 7 ).…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, few malaria TPPs consider operational aspects such as deployment coverage in addition to product-specific characteristics such as efficacy or half-life. This has implications for the appropriate definition of intervention effectiveness characteristics according to local health systems and health targets (46, 51, 52). Given the large amount of malaria interventions currently in the development pipeline, a systematic approach is essential to inform development decisions and prioritization of novel interventions to ensure a sustainable investment of resources and a fast pace of innovation.…”

Section: Introductionmentioning

confidence: 99%

Leveraging mathematical models of disease dynamics and machine learning to improve development of novel malaria interventions

Golumbeanu

Yang

Stuckey

et al. 2021

Preprint

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The development of novel interventions against a disease entails optimising their specifications to achieve desired health goals such as disease reduction. As testing is limited early in development, it is difficult to predefine these optimal specifications, prioritize or continue investment in candidate interventions. Mathematical models of disease can provide quantitative evidence as they can simulate deployment and predict impact of a new intervention considering deployment, health-system, population and disease characteristics. However, due to large uncertainty early in development, as well as model complexity, testing all possible combinations of interventions and deployments becomes infeasible. As a result, mathematical models have been only marginally used during intervention development to date. Here, we present a new approach where machine learning enables the use of detailed disease models to identify optimal properties of candidate interventions to reach a desired health goal and guide development. We demonstrate the power of our approach by application to five novel malaria interventions under development. For various targeted reductions of malaria prevalence, we quantify and rank intervention characteristics which are key determinants of health impact. Furthermore, we identify minimal requirements and tradeoffs between operational factors, intervention efficacy and duration to achieve different levels of impact and show how these vary across disease transmission settings. When single interventions cannot achieve significant impact, our method allows finding optimal combinations of interventions fulfilling the desired health goals. By enabling efficient use of disease models, our approach supports decision-making and resource investment in the development of new interventions for infectious diseases.Significance StatementDuring development of novel disease interventions (e.g. vaccines), a target product profile (TPP) document defines intervention characteristics required to meet health goals. As clinical trials are limited early in development, mathematical models simulating disease dynamics can help define TPPs. However, testing all combinations of intervention, delivery and environment characteristics is infeasible and so complex mathematical models have not been used until now. We introduce a new approach to define TPPs, combining models of disease with machine learning. We examined several novel malaria interventions, identifying key characteristics, minimum efficacy and duration of effect that ensure significant reductions in malaria prevalence. This approach therefore enabled mathematical models of disease to support intervention development, by identifying intervention requirements that ensure public health impact.One Sentence SummaryDefining quantitative profiles of novel disease interventions by combining machine learning with mathematical models of disease transmission

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International survey to identify diagnostic needs to support malaria elimination: guiding the development of combination highly sensitive rapid diagnostic tests

Campillo

Daily

González

2017

Malar J

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BackgroundIn malaria elimination settings, the very low levels of transmission now being attained present challenges that demand new strategies to identify and treat low-density infections in both symptomatic and asymptomatic populations. Accordingly, passive case detection activities need to be supplemented by active case detection (ACD) strategies with more sensitive diagnostic tools. Malaria rapid diagnostic tests (RDTs) have provided low- and middle-income countries with unprecedented access to malaria diagnostics. Nevertheless, conventional RDTs miss a potentially important proportion of sub-microscopic infections. Therefore, new combination highly sensitive (HS-)RDTs, able to detect low parasite densities and identify all infected individuals, could support countries implementing ACD strategies for radical cure to accelerate malaria elimination. To address this need, an on-line survey was conducted to gather information from malaria control programme representatives to guide the development of next-generation RDTs.ResultsMost of respondents confirmed that ACD was a common activity in their programmes (56/75; 75%). Although microscopy was the preferred method in case management and reactive case detection, RDTs were the primary diagnostic tests used in proactive case detection (31/75; 41%). In terms of preferences for species detection in a new combination HS-RDT, data was not one-directional. Survey respondents slightly preferred the Pf/Pv/Pan combination (42%; 21/50), while Pf/Pan was more popular among end-users. Survey respondents also valued a low-cost (< $1.00 USD), lightweight and portable test, able to detect asymptomatic infections and differentiate species, as well as provide immediate results that could be interpreted with the naked eye. In addition, respondents were open to new tests and even to replace the existing ones for ACD (63%; 47/75).ConclusionsThis survey provided valuable information on the use and current limitations of ACD, on the primary product characteristics for a next-generation combination HS-RDT to support ACD and radical cure, and on the potential adoption of such a test, if available, to support malaria elimination.

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Incorporating user needs into product development for improved infection detection for malaria elimination programs

Cited by 5 publications

References 19 publications

Target Product Profiles for medical tests: a systematic review of current methods

Target Product Profiles for medical tests: a systematic review of current methods

Leveraging mathematical models of disease dynamics and machine learning to improve development of novel malaria interventions

International survey to identify diagnostic needs to support malaria elimination: guiding the development of combination highly sensitive rapid diagnostic tests

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