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

Facilitating the use of the target product profile in academic research: a systematic review

BACKGROUND

The Target Product Profile (TPP) is a tool used in industry to guide development strategies by addressing user needs and fostering effective communication among stakeholders. However, they are not frequently used in academic research, where they may be equally useful. This systematic review aims to extract the features of accessible TPPs, to identify commonalities and facilitate their integration in academic research methodology.

METHODS

We searched peer-reviewed papers published in English developing TPPs for different products and health conditions in four biomedical databases. Interrater agreement, computed on random abstract and paper sets (Cohen's Kappa; percentage agreement with zero tolerance) was > 0.91. We interviewed experts from industry contexts to gain insight on the process of TPP development, and extracted general and specific features on TPP use and structure.

RESULTS

138 papers were eligible for data extraction. Of them, 92% (n = 128) developed a new TPP, with 41.3% (n = 57) focusing on therapeutics. The addressed disease categories were diverse; the largest (47.1%, n = 65) was infectious diseases. Only one TPP was identified for several fields, including global priorities like dementia. Our analyses found that 56.5% of papers (n = 78) was authored by academics, and 57.8% of TPPs (n = 80) featured one threshold level of product performance. The number of TPP features varied widely across and within product types (n = 3-44). Common features included purpose/context of use, shelf life for drug stability and validation aspects. Most papers did not describe the methods used to develop the TPP. We identified aspects to be taken into account to build and report TPPs, as a starting point for more focused initiatives guiding use by academics.

DISCUSSION

TPPs are used in academic research mostly for infectious diseases and have heterogeneous features. Our extraction of key features and common structures helps to understand the tool and widen its use in academia. This is of particular relevance for areas of notable unmet needs, like dementia. Collaboration between stakeholders is key for innovation. Tools to streamline communication such as TPPs would support the development of products and services in academia as well as industry.

Outcome-based analytical performance specifications: current status and future challenges

Analytical performance specifications (APS) based on outcomes refer to how 'good' the analytical performance of a test needs to be to do more good than harm to the patient. Analytical performance of a measurand affects its clinical performance. Without first setting clinical performance requirements, it is difficult to define how good analytically the test needs to be to meet medical needs. As testing is indirectly linked to health outcomes through clinical decisions on patient management, often simulation-based studies are used to assess the impact of analytical performance on the probability of clinical outcomes which is then translated to Model 1b APS according to the Milan consensus. This paper discusses the related key definitions, concepts and considerations that should assist in finding the most appropriate methods for deriving Model 1b APS. We review the advantages and limitations of published methods and discuss the criteria for transferability of Model 1b APS to different settings. We consider that the definition of the clinically acceptable misclassification rate is central to Model 1b APS. We provide some examples and guidance on a more systematic approach for first defining the clinical performance requirements for tests and we also highlight a few ideas to tackle the future challenges associated with providing outcome-based APS for laboratory testing.

Advancing Colorectal Cancer Detection With Blood-Based Tests: Qualitative Study and Discrete Choice Experiment to Elicit Population Preferences

BACKGROUND

Colorectal cancer (CRC) is the second most deadly form of cancer, inducing an estimated 1.9 million incidence cases and 0.9 million deaths worldwide in 2020. Despite the availability of screening tests, their uptake remains suboptimal. However, blood-based tests that look for signs of cancer-specific markers in the body are increasingly available as an alternative for more invasive tests for cancer. Compared with existing tests, the benefits of blood-based tests for CRC include not needing pretest preparation, stool handling, and dietary or medication restrictions.

OBJECTIVE

This study aims to explore the population's preferences for CRC screening tests, with a focus on blood-based tests, and investigate the factors influencing test uptake.

METHODS

We used a mixed methods approach, combining semistructured interviews and a discrete choice experiment (DCE) survey. Interviews were analyzed using thematic analysis to identify salient attributes for CRC screening tests. These attributes informed the design of the DCE survey. The DCE data were analyzed using mixed logit and mixed-mixed multinomial logit models.

RESULTS

Qualitative findings from 30 participants revealed that participants preferred blood-based tests due to their perceived low risk, minimal pain, and ease of sample collection. However, concerns about the test's lower accuracy were also expressed. The DCE survey was completed by 1189 participants. In the mixed logit model, participants demonstrated a stronger preference for blood-based tests over a 2-day stool-based test. The mixed-mixed multinomial logit model identified 2 classes, strong supporters and weak supporters, for CRC screening. Weak supporters, but not strong supporters, had a higher preference for blood-based tests. Women, ethnic Chinese, and people aged 40 to 60 years were more likely to be weak supporters. Both models highlighted the high influence of cost and test sensitivity on participants' preferences. Transitioning from a 2-day stool-based test to a blood-based test, assuming a national screening program at a base price of Singapore $5 (US $3.75), was estimated to have the potential to increase the relative uptake by 5.9% (95% CI 3.6%-8.2%).

CONCLUSIONS

These findings contribute to our understanding of CRC screening preferences and provide insights into the factors driving test uptake. This study highlights the perceived advantages of blood-based tests and identifies areas of concern regarding their accuracy. Further research is needed to determine the actual increase in uptake rate when blood-based tests are made available.

"Notification! You May Have Cancer." Could Smartphones and Wearables Help Detect Cancer Early?

This viewpoint paper considers the authors' perspectives on the potential role of smartphones, wearables, and other technologies in the diagnosis of cancer. We believe that these technologies could be valuable additions in the pursuit of early cancer diagnosis, as they offer solutions to the timely detection of signals or symptoms and monitoring of subtle changes in behavior that may otherwise be missed. In addition to signal detection, technologies could assist symptom interpretation and guide and facilitate access to health care. This paper aims to provide an overview of the scientific rationale as to why these technologies could be valuable for early cancer detection, as well as outline the next steps for research and development to drive investigation into the potential for smartphones and wearables in this context and optimize implementation. We draw attention to potential barriers to successful implementation, including the difficulty of the development of signals and sensors with sufficient utility and accuracy through robust research with the target group. There are regulatory challenges; the potential for innovations to exacerbate inequalities; and questions surrounding acceptability, uptake, and correct use by the intended target group and health care practitioners. Finally, there is potential for unintended consequences on individuals and health care services including unnecessary anxiety, increased symptom burden, overinvestigation, and inappropriate use of health care resources.

Target Product Profile for a Machine Learning-Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study

BACKGROUND

Diabetic eye screening (DES) represents a significant opportunity for the application of machine learning (ML) technologies, which may improve clinical and service outcomes. However, successful integration of ML into DES requires careful product development, evaluation, and implementation. Target product profiles (TPPs) summarize the requirements necessary for successful implementation so these can guide product development and evaluation.

OBJECTIVE

This study aims to produce a TPP for an ML-automated retinal imaging analysis software (ML-ARIAS) system for use in DES in England.

METHODS

This work will consist of 3 phases. Phase 1 will establish the characteristics to be addressed in the TPP. A list of candidate characteristics will be generated from the following sources: an overview of systematic reviews of diagnostic test TPPs; a systematic review of digital health TPPs; and the National Institute for Health and Care Excellence's Evidence Standards Framework for Digital Health Technologies. The list of characteristics will be refined and validated by a study advisory group (SAG) made up of representatives from key stakeholders in DES. This includes people with diabetes; health care professionals; health care managers and leaders; and regulators and policy makers. In phase 2, specifications for these characteristics will be drafted following a series of semistructured interviews with participants from these stakeholder groups. Data collected from these interviews will be analyzed using the shortlist of characteristics as a framework, after which specifications will be drafted to create a draft TPP. Following approval by the SAG, in phase 3, the draft will enter an internet-based Delphi consensus study with participants sought from the groups previously identified, as well as ML-ARIAS developers, to ensure feasibility. Participants will be invited to score characteristic and specification pairs on a scale from "definitely exclude" to "definitely include," and suggest edits. The document will be iterated between rounds based on participants' feedback. Feedback on the draft document will be sought from a group of ML-ARIAS developers before its final contents are agreed upon in an in-person consensus meeting. At this meeting, representatives from the stakeholder groups previously identified (minus ML-ARIAS developers, to avoid bias) will be presented with the Delphi results and feedback of the user group and asked to agree on the final contents by vote.

RESULTS

Phase 1 was completed in November 2023. Phase 2 is underway and expected to finish in March 2024. Phase 3 is expected to be complete in July 2024.

CONCLUSIONS

The multistakeholder development of a TPP for an ML-ARIAS for use in DES in England will help developers produce tools that serve the needs of patients, health care providers, and their staff. The TPP development process will also provide methods and a template to produce similar documents in other disease areas.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/50568.

Involving patients in drug development for Neglected Tropical Diseases (NTDs): A qualitative study exploring and incorporating preferences of patients with cutaneous leishmaniasis into Target Product Profile development

BACKGROUND

Target Product Profiles (TPPs) are instrumental to help optimise the design and development of therapeutics, vaccines, and diagnostics - these products, in order to achieve the intended impact, should be aligned with users' preferences and needs. However, patients are rarely involved as key stakeholders in building a TPP.

METHODOLOGY

Thirty-three cutaneous leishmaniasis (CL) patients from Brazil, Colombia, and Austria, infected with New-World Leishmania species, were recruited using a maximum variation approach along geographic, sociodemographic and clinical criteria. Semi-structured interviews were conducted in the respective patient's mother tongue. Transcripts, translated into English, were analysed using a framework approach. We matched disease experiences, preferences, and expectations of CL patients to a TPP developed by DNDi (Drug for Neglected Diseases initiative) for CL treatment.

PRINCIPAL FINDINGS

Patients' preferences regarding treatments ranged from specific efficacy and safety endpoints to direct and significant indirect costs. Respondents expressed views about trade-offs between efficacy and experienced discomfort/adverse events caused by treatment. Reasons for non-compliance, such as adverse events or geographical and availability barriers, were discussed. Considerations related to accessibility and affordability were relevant from the patients' perspective.

CONCLUSIONS/SIGNIFICANCE

NTDs affect disadvantaged populations, often with little access to health systems. Engaging patients in designing adapted therapies could significantly contribute to the suitability of an intervention to a specific context and to compliance, by tailoring the product to the end-users' needs. This exploratory study identified preferences in a broad international patient spectrum. It provides methodological guidance on how patients can be meaningfully involved as stakeholders in the construction of a TPP of therapeutics for NTDs. CL is used as an exemplar, but the approach can be adapted for other NTDs.

Insights into implementation planning for point-of-care testing to guide treatment of chronic obstructive pulmonary disease exacerbation: a mixed methods feasibility study

The purpose of this mixed methods feasibility study was to gain insights into unmet clinical needs, stakeholder preferences and potential barriers and enablers to adoption for planning the implementation of point-of-care testing for earlier detection and guided treatment of chronic obstructive pulmonary disease (COPD) acute exacerbation in the NHS in England. Exacerbations of COPD cause considerable mortality and morbidity. Earlier identification of exacerbations and guided treatment would lead to reduced exacerbation duration, reduced hospitalizations and mortality, improve health-related quality of life, reduce unnecessary treatments (including inappropriate antibiotic prescribing) which could save the NHS over £400 per patient. During the early stages of product design, we took a multi-disciplinary approach to evidence generation, gaining insights from key stakeholders to test the product concept and inform evidence-based implementation planning. Primary data was collected from 11 health care and service professionals involved in the management of acute COPD exacerbations. Overall, participants agreed that by earlier differentiation of acute exacerbation from stable COPD, patients could be started on appropriate treatment. To implement point-of-care testing into clinical practice, evidence is required to demonstrate the accuracy of differentiating between exacerbation etiologies and to provide information on the beneficial impact to the system in terms of optimized management, reduced long-term side effects, admission avoidance, and cost-effectiveness. This research provides an evidence base for future implementation planning of point-of-care testing for earlier detection and guided treatment of COPD acute exacerbation. Moreover, the technology developers can decide whether to refine the product design and value proposition thereby de-risking product development.

Expert consensus on novel medicines to prevent preterm birth and manage preterm labour: Target product profiles

OBJECTIVE

To develop target product profiles (TPPs) for new medicines for preterm birth prevention and preterm labour management that address the real-world need of women and healthcare providers, informed by views and agreement amongst globally diverse stakeholders.

DESIGN

Mixed methods.

SETTING

Global (with a focus on low- and middle-income countries, LMICs).

SAMPLE

Global stakeholders with diverse expertise in preterm labour/birth and drug development.

METHODS

Following an initial literature review, diverse stakeholders were invited to participate in an online international survey and in-depth interviews. The level of stakeholder agreement with TPPs was assessed, and findings from interviews were synthesised to inform the final TPPs.

MAIN OUTCOMES MEASURES

Level of stakeholder agreement on the minimum and preferred requirements for preterm labour/birth medicines.

RESULTS

We performed 21 interviews. Interview participants demonstrated strong agreement on room temperature stability, no additional drug-specific clinical monitoring, and affordability in LMICs being the minimal acceptable requirements. Points of discussion were raised around the target population. Survey respondents included clinicians, researchers, funding agency staff, international public organisation staff, programme implementers, policymakers, representatives of consumer advocacy organisations and other relevant stakeholders from maternal health systems. Survey results indicated strong agreement amongst stakeholders, with only one variable in each TPP not reaching consensus (i.e. 25% disagree or strongly disagree).

CONCLUSIONS

There is strong consensus within the preterm labour/birth community on the characteristics that new medicines for preterm birth prevention and preterm labour management must achieve. These TPPs provide necessary guidance to evaluate new candidates and their potential for implementation in a range of settings.

Quality by Design Perspective for Designing Foam-based Formulation: Current State of Art

Foam-based delivery systems contain one or more active ingredients and dispersed solid or liquid components that transform into gaseous form when the valve is actuated. Foams are an attractive and effective delivery approach for medical, cosmetic, and pharmaceutical uses. The foams-based delivery systems are gaining attention due to ease of application as they allow direct application onto the affected area of skin without using any applicator or finger, hence increasing the compliance and satisfaction of the patients. In order to develop foam-based delivery systems with desired qualities, it is vital to understand which type of material and process parameters impact the quality features of foams and which methodologies may be utilized to investigate foams. For this purpose, Quality-by-Design (QbD) approach is used. It aids in achieving quality-based development during the development process by employing the QbD concept. The critical material attributes (CMAs) and critical process parameters (CPPs) were discovered through the first risk assessment to ensure the requisite critical quality attributes (CQAs). During the initial risk assessment, the high-risk CQAs were identified, which affect the foam characteristics. In this review, the authors discussed the various CMAs, CPPs, CQAs, and risk factors associated in order to develop an ideal foam-based formulation with desired characteristics.

Expert guidance on target product profile development for AMR diagnostic tests

Diagnostics are widely considered crucial in the fight against antimicrobial resistance (AMR), which is expected to kill 10 million people annually by 2030. Nevertheless, there remains a substantial gap between the need for AMR diagnostics versus their development and implementation. To help address this problem, target product profiles (TPP) have been developed to focus developers' attention on the key aspects of AMR diagnostic tests. However, during discussion between a multisectoral working group of 51 international experts from industry, academia and healthcare, it was noted that specific AMR-related TPPs could be extended by incorporating the interdependencies between the key characteristics associated with the development of such TPPs. Subsequently, the working group identified 46 characteristics associated with six main categories (ie, Intended Use, Diagnostic Question, Test Description, Assay Protocol, Performance and Commercial). The interdependencies of these characteristics were then identified and mapped against each other to generate new insights for use by stakeholders. Specifically, it may not be possible for diagnostics developers to achieve all of the recommendations in every category of a TPP and this publication indicates how prioritising specific TPP characteristics during diagnostics development may influence (or not) a range of other TPP characteristics associated with the diagnostic. The use of such guidance, in conjunction with specific TPPs, could lead to more efficient AMR diagnostics development.

Care Pathway Analysis to Inform the Earliest Stages of Technology Development: Scoping Oncological Indications in Need of Innovation

OBJECTIVES

Identifying unmet needs for innovative solutions across disease contexts is challenging but important for directing funding and research efforts and informing early-stage decisions during the innovation process. Our aim was to study the merits of care pathway analysis to scope disease contexts and guide the development of innovative devices. We used oncologic surgery as a case study, for which many intraoperative imaging techniques are under development.

METHODS

Care pathway analysis is a mapping process, which produces graphical maps of clinical pathways using important outcomes and subsequent consequences. We performed care pathway analyses for glioblastoma, breast, bladder, prostate, renal, pancreatic, and oral cavity cancer. Differences between a "perfect" care pathway and the current care pathway in terms of percentage of inadequate margins, associated recurrences, quality of life, and 5-year overall survival were calculated to determine unmet needs. Data from The Netherlands Cancer Registry and literature were used.

RESULTS

Care pathway analysis showed that highest percentages of inadequate margins were found in oral cavity cancer (72.5%), glioblastoma (48.7%), and pancreatic cancer (43.9%). Inadequate margins showed the strongest increase in recurrences in cancer of oral cavity, and bladder (absolute increases of 43.5% and 41.2%, respectively). Impact on survival was largest for bladder and oral cavity cancer with positive margins.

CONCLUSIONS

Care pathway analysis provides overviews of current clinical paths in multiple indications. Disease contexts can be compared via effectiveness gaps that show the potential need for innovative solutions. This information can be used as basis for stakeholder involvement processes to prioritize care pathways in need of innovation.

Target product profiles for neonatal care devices: systematic development and outcomes with NEST360 and UNICEF

BACKGROUND

Medical devices are critical to providing high-quality, hospital-based newborn care, yet many of these devices are unavailable in low- and middle-income countries (LMIC) and are not designed to be suitable for these settings. Target Product Profiles (TPPs) are often utilised at an early stage in the medical device development process to enable user-defined performance characteristics for a given setting. TPPs can also be applied to assess the profile and match of existing devices for a given context.

METHODS

We developed initial TPPs for 15 newborn product categories for LMIC settings. A Delphi-like process was used to develop the TPPs. Respondents completed an online survey where they scored their level of agreement with each of the proposed performance characteristics for each of the 15 devices. Characteristics with < 75% agreement between respondents were discussed and voted on using Mentimeter™ at an in-person consensus meeting.

FINDINGS

The TPP online survey was sent to 180 people, of which 103 responded (57%). The majority of respondents were implementers/clinicians (51%, 53/103), with 50% (52/103) from LMIC. Across the 15 TPPs, 403 (60%) of the 668 performance characteristics did not achieve > 75% agreement. Areas of disagreement were voted on by 69 participants at an in-person consensus meeting, with consensus achieved for 648 (97%) performance characteristics. Only 20 (3%) performance characteristics did not achieve consensus, most (15/20) relating to quality management systems. UNICEF published the 15 TPPs in April 2020, accompanied by a report detailing the online survey results and consensus meeting discussion, which has been viewed 7,039 times (as of January 2023).

CONCLUSIONS

These 15 TPPs can inform developers and enable implementers to select neonatal care products for LMIC. Over 2,400 medical devices and diagnostics meeting these TPPs have been installed in 65 hospitals in Nigeria, Tanzania, Kenya, and Malawi through the NEST360 Alliance. Twenty-three medical devices identified and qualified by NEST360 meet nearly all performance characteristics across 11 of the 15 TPPs. Eight of the 23 qualified medical devices are available in the UNICEF Supply Catalogue. Some developers have adjusted their technologies to meet these TPPs. There is potential to adapt the TPP process beyond newborn care.

Clinical needs assessment to inform development of a new assay to detect antimalarial drugs in patient samples: A case study

Point-of-care assays have greatly increased access to diagnostic information and improved healthcare outcomes globally, especially in the case of tropical diseases in rural settings. Increased recognition of the impact of these tools and increased funding, along with advances in technology have led to a surge in development of new assays. However, many new tools fail to fulfill their intended purpose due to a lack of clinical impact, operational feasibility, and input from envisioned operators. To be successful, they must fit into existing clinical decision-making models and be designed in collaboration with end users. We describe a case study of the development of a new low-cost sensor for antimalarial drugs, from initial planning through collection and incorporation of design feedback to final assay design. The assay uses an aptamer-based sensor to detect antimalarial drugs from patient samples for tracking antimalarial use in Southeast Asia, a region with a long history of emerging antimalarial drug resistance. Design and use-case input was collected from malaria control experts, researchers, and healthcare workers to develop target product profiles. Data was collected via surveys and in-person interviews during assay development and ultimately informed a change in assay format. This aptamer sensor platform can be easily adapted to detect other small molecule and protein targets and the design process described here can serve as a model for the development of effective new assays to improve access to healthcare technology.

Respiratory metagenomics: route to routine service

PURPOSE OF REVIEW

The coronavirus disease 2019 pandemic demonstrated broad utility of pathogen sequencing with rapid methodological progress alongside global distribution of sequencing infrastructure. This review considers implications for now moving clinical metagenomics into routine service, with respiratory metagenomics as the exemplar use-case.

RECENT FINDINGS

Respiratory metagenomic workflows have completed proof-of-concept, providing organism identification and many genotypic antimicrobial resistance determinants from clinical samples in <6 h. This enables rapid escalation or de-escalation of empiric therapy for patient benefit and reducing selection of antimicrobial resistance, with genomic-typing available in the same time-frame. Attention is now focussed on demonstrating clinical, health-economic, accreditation, and regulatory requirements. More fundamentally, pathogen sequencing challenges the traditional culture-orientated time frame of microbiology laboratories, which through automation and centralisation risks becoming increasingly separated from the clinical setting. It presents an alternative future where infection experts are brought together around a single genetic output in an acute timeframe, aligning the microbiology target operating model with the wider human genomic and digital strategy.

SUMMARY

Pathogen sequencing is a transformational proposition for microbiology laboratories and their infectious diseases, infection control, and public health partners. Healthcare systems that link output from routine clinical metagenomic sequencing, with pandemic and antimicrobial resistance surveillance, will create valuable tools for protecting their population against future infectious diseases threats.

Modelling the Cost-Effectiveness of Diagnostic Tests

Diagnostic tests are used to determine whether a disease or condition is present or absent in a patient, who will typically be suspected of having the disease or condition due to symptoms or clinical signs. Economic evaluations of diagnostic tests (e.g. cost-effectiveness analyses) can be used to determine whether a test produces sufficient benefit to justify its cost. Evidence on the benefits conferred by a test is often restricted to its accuracy, which means mathematical models are required to estimate the impact of a test on outcomes that matter to patients and health payers. It is important to realise the case for introducing a new test may not be restricted to its accuracy, but extend to factors such as time to diagnosis and acceptability for patients. These and other considerations may mean the common modelling approach, the decision tree, is inappropriate for underpinning an economic evaluation. There are no consensus guidelines on how economic evaluations of diagnostic tests should be conducted-this article attempts to explore the common challenges encountered in economic evaluations, suggests solutions to those challenges, and identifies some areas where further methodological work may be necessary.

Frameworks for Health Technology Assessment at an Early Stage of Product Development: A Review and Roadmap to Guide Applications

OBJECTIVES

Early health technology assessment (eHTA) can be used to evaluate and optimize a medical product's value proposition and to inform go/no-go decisions by using health economic modeling, literature scanning, and stakeholder preference studies at an early stage of development. eHTA frameworks offer high-level guidance on conducting this complex, iterative, and multidisciplinary process. The objective of this study was to review and summarize existing eHTA frameworks, understood as systematic approaches to guide early evidence generation and decision making.

METHODS

Using a rapid review methodology, we identified all relevant studies published in English, French, and Spanish from PubMed/MEDLINE and Embase until February 2022. We only included frameworks relevant to the preclinical and early clinical (phase I) stages of medical product development.

RESULTS

From 737 reviewed abstracts, 53 publications describing 46 frameworks were selected for inclusion and classified into categories based on their scope: (1) criteria frameworks, which provide an overview of eHTA; (2) process frameworks, which offer stepwise guidance for conducting eHTA, including preferred methods; and (3) methods frameworks, which provide detailed descriptions of specific eHTA methods. Most of the frameworks did not specify their target users or the specific stage of technology development.

CONCLUSIONS

Despite some variability and gaps found across existing frameworks, the structure provided by this review helps inform eHTA applications. Remaining challenges are the frameworks' limited accessibility to users without a background in health economics, poor distinctions being made among early lifecycle stages and technology types, and the inconsistent terminology used to describe eHTA in different contexts.

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

Background

Substantial research is underway to develop next-generation interventions that address current malaria control challenges. As there is limited testing in their early development, it is difficult to predefine intervention properties such as efficacy that achieve target health goals, and therefore challenging to prioritize selection of novel candidate interventions. Here, we present a quantitative approach to guide intervention development using mathematical models of malaria dynamics coupled with machine learning. Our analysis identifies requirements of efficacy, coverage, and duration of effect for five novel malaria interventions to achieve targeted reductions in malaria prevalence.

Methods

A mathematical model of malaria transmission dynamics is used to simulate deployment and predict potential impact of new malaria interventions by considering operational, health-system, population, and disease characteristics. Our method relies on consultation with product development stakeholders to define the putative space of novel intervention specifications. We couple the disease model with machine learning to search this multi-dimensional space and efficiently identify optimal intervention properties that achieve specified health goals.

Results

We apply our approach to five malaria interventions under development. Aiming for malaria prevalence reduction, we identify and quantify key determinants of intervention impact along with their minimal properties required to achieve the desired health goals. While coverage is generally identified as the largest driver of impact, higher efficacy, longer protection duration or multiple deployments per year are needed to increase prevalence reduction. We show that interventions on multiple parasite or vector targets, as well as combinations the new interventions with drug treatment, lead to significant burden reductions and lower efficacy or duration requirements.

Conclusions

Our approach uses disease dynamic models and machine learning to support decision-making and resource investment, facilitating development of new malaria interventions. By evaluating the intervention capabilities in relation to the targeted health goal, our analysis allows prioritization of interventions and of their specifications from an early stage in development, and subsequent investments to be channeled cost-effectively towards impact maximization. This study highlights the role of mathematical models to support intervention development. Although we focus on five malaria interventions, the analysis is generalizable to other new malaria interventions.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-022-00981-1.

The potential of digital molecular diagnostics for infectious diseases in sub-Saharan Africa

There is a large gap between diagnostic needs and diagnostic access across much of sub-Saharan Africa (SSA), particularly for infectious diseases that inflict a substantial burden of morbidity and mortality. Accurate diagnostics are essential for the correct treatment of individuals and provide vital information underpinning disease surveillance, prevention, and control strategies. Digital molecular diagnostics combine the high sensitivity and specificity of molecular detection with point-of-care format and mobile connectivity. Recent developments in these technologies create an opportunity for a radical transformation of the diagnostic ecosystem. Rather than trying to emulate diagnostic laboratory models in resource-rich settings, African countries have the potential to pioneer new models of healthcare designed around digital diagnostics. This article describes the need for new diagnostic approaches, highlights advances in digital molecular diagnostic technology, and outlines their potential for tackling infectious diseases in SSA. It then addresses the steps that will be necessary for the development and implementation of digital molecular diagnostics. Although the focus is on infectious diseases in SSA, many of the principles apply to other resource-limited settings and to noncommunicable diseases.

Accuracy of computer-aided chest X-ray in community-based tuberculosis screening: Lessons from the 2016 Kenya National Tuberculosis Prevalence Survey

Community-based screening for tuberculosis (TB) could improve detection but is resource intensive. We set out to evaluate the accuracy of computer-aided TB screening using digital chest X-ray (CXR) to determine if this approach met target product profiles (TPP) for community-based screening. CXR images from participants in the 2016 Kenya National TB Prevalence Survey were evaluated using CAD4TBv6 (Delft Imaging), giving a probabilistic score for pulmonary TB ranging from 0 (low probability) to 99 (high probability). We constructed a Bayesian latent class model to estimate the accuracy of CAD4TBv6 screening compared to bacteriologically-confirmed TB across CAD4TBv6 threshold cut-offs, incorporating data on Clinical Officer CXR interpretation, participant demographics (age, sex, TB symptoms, previous TB history), and sputum results. We compared model-estimated sensitivity and specificity of CAD4TBv6 to optimum and minimum TPPs. Of 63,050 prevalence survey participants, 61,848 (98%) had analysable CXR images, and 8,966 (14.5%) underwent sputum bacteriological testing; 298 had bacteriologically-confirmed pulmonary TB. Median CAD4TBv6 scores for participants with bacteriologically-confirmed TB were significantly higher (72, IQR: 58-82.75) compared to participants with bacteriologically-negative sputum results (49, IQR: 44-57, p<0.0001). CAD4TBv6 met the optimum TPP; with the threshold set to achieve a mean sensitivity of 95% (optimum TPP), specificity was 83.3%, (95% credible interval [CrI]: 83.0%-83.7%, CAD4TBv6 threshold: 55). There was considerable variation in accuracy by participant characteristics, with older individuals and those with previous TB having lowest specificity. CAD4TBv6 met the optimal TPP for TB community screening. To optimise screening accuracy and efficiency of confirmatory sputum testing, we recommend that an adaptive approach to threshold setting is adopted based on participant characteristics.

Target product profiles for novel medicines to prevent and treat preeclampsia: An expert consensus

BACKGROUND

Preeclampsia and eclampsia are a leading cause of global maternal and newborn mortality. Currently, there are few effective medicines that can prevent or treat preeclampsia. Target Product Profiles (TPPs) are important tools for driving new product development by specifying upfront the characteristics that new products should take. Considering the lack of investment and innovation around new medicines for obstetric conditions, we aimed to develop two new TPPs for medicines to prevent and treat preeclampsia.

METHODS AND FINDINGS

We used a multi-methods approach comprised of a literature review, stakeholder interviews, online survey, and public consultation. Following an initial literature review, diverse stakeholders (clinical practice, research, academia, international organizations, funders, consumer representatives) were invited for in-depth interviews and an online international survey, as well as public consultation on draft TPPs. The level of stakeholder agreement with TPPs was assessed, and findings from interviews were synthesised to inform the final TPPs. We performed 23 stakeholder interviews and received 46 survey responses. A high level of agreement was observed in survey results, with 89% of TPP variables reaching consensus (75% agree or strongly agree). Points of discussion were raised around the target population for preeclampsia prevention and treatment, as well as the acceptability of cold-chain storage and routes of administration.

CONCLUSION

There is consensus within the maternal health research community on the parameters that new medicines for preeclampsia prevention and treatment must achieve to meet real-world health needs. These TPPs provide necessary guidance to spur interest, innovation and investment in the development of new medicines to prevent and treat preeclampsia.

COVID-19 rapid diagnostics: practice review

Point-of-care tests for SARS-CoV-2 could enable rapid rule-in and/or rule-out of COVID-19, allowing rapid and accurate patient cohorting and potentially reducing the risk of nosocomial transmission. As COVID-19 begins to circulate with other more common respiratory viruses, there is a need for rapid diagnostics to help clinicians test for multiple potential causative organisms simultaneously.However, the different technologies available have strengths and weaknesses that must be understood to ensure that they are used to the benefit of the patient and healthcare system. Device performance is related to the deployed context, and the diagnostic characteristics may be affected by user experience.This practice review is written by members of the UK's COVID-19 National Diagnostic Research and Evaluation programme. We discuss relative merits and test characteristics of various commercially available technologies. We do not advocate for any given test, and our coverage of commercially supplied tests is not intended to be exhaustive.

Integrating Early Economic Evaluation into Target Product Profile development for medical tests: advantages and potential applications

Target Product Profiles (TPPs) outline the characteristics that new health technologies require to address an unmet clinical need. To date, published TPPs for medical tests have focused on infectious diseases, mostly in the context of low- and middle-income countries. Recently, there have been calls for a broader use of TPPs as a mechanism to ensure that diagnostic innovation is aligned with clinical needs, yet the methodology underpinning TPP development remains suboptimal. Here, we propose that early economic evaluation (EEE) should be integrated within the TPP methodology to create a more rigorous framework for the development of "fit-for-purpose" tests. We discuss the potential benefits that EEE could bring to the core activities underpinning TPP development-scoping, drafting, consensus building, and updating-and argue that using EEE to help inform TPPs provides a more objective, evidence-based, and transparent approach to defining test specifications.

Electrochemical sensing of blood proteins for mild traumatic brain injury (mTBI) diagnostics and prognostics: towards a point-of-care application

Traumatic Brain Injury (TBI) being one of the principal causes of death and acquired disability in the world imposes a large burden on the global economy. Mild TBI (mTBI) is particularly challenging to assess due to the frequent lack of well-pronounced post-injury symptoms. However, if left untreated mTBI (especially when repetitive) can lead to serious long-term implications such as cognitive and neuropathological disorders. Computer tomography and magnetic resonance imaging commonly used for TBI diagnostics require well-trained personnel, are costly, difficult to adapt for on-site measurements and are not always reliable in identifying small brain lesions. Thus, there is an increasing demand for sensitive point-of-care (POC) testing tools in order to aid mTBI diagnostics and prediction of long-term effects. Biomarker quantification in body fluids is a promising basis for POC measurements, even though establishing a clinically relevant mTBI biomarker panel remains a challenge. Actually, a minimally invasive, rapid and reliable multianalyte detection device would allow the efficient determination of injury biomarker release kinetics and thus support the preclinical evaluation and clinical validation of a proposed biomarker panel for future decentralized in vitro diagnostics. In this respect electrochemical biosensors have recently attracted great attention and the present article provides a critical study on the electrochemical protocols suggested in the literature for detection of mTBI-relevant protein biomarkers. The authors give an overview of the analytical approaches for transduction element functionalization, review recent technological advances and highlight the key challenges remaining in view of an eventual integration of the proposed concepts into POC diagnostic solutions.

Rapid point-of-care testing for COVID-19: quality of supportive information for lateral flow serology assays

OBJECTIVE

There is a lack of evidence addressing several important human factors questions pertaining to the quality of supportive information provided by commercial manufacturers that can affect the adoption and use of lateral flow serology assays in practice. We aimed to: (1) identify and assess the quality of information that commercial manufacturers provided for their point-of-care tests (POCTs) and (2) examine the implications of these findings on real-world settings.

DESIGN

We used a content analysis methodology in two stages to systematically, code and analyse textual data from documents of commercial manufacturers. A deductive approach was applied using a coding guide based on the validated Point-of-Care Key Evidence Tool (POCKET) multidimensional checklist. An inductive approach was used to identify new patterns or themes generated from our textual analysis.

SETTING

Publicly available supportive information documents by commercial manufacturers for lateral flow serology, were identified and gathered from online searches.

PARTICIPANTS

Supportive information documents retrieved from online searches over 3 months (March 2020 to June 2020).

RESULTS

A total of 79 POCTs were identified that met the study inclusion criteria. Using the POCKET coding guide, we found that the quality of information varied significantly between the manufacturers and was often lacking in detail. Our inductive approach further examined these topics and found that several statements were vague and that significant variations in the level of details existed between manufacturers.

CONCLUSIONS

This study revealed significant concerns surrounding the supportive information reported by manufacturers for lateral flow serology assays. Information transparency was poor and human factor issues were not properly addressed to mitigate the risk of improper device use, although it should be noted that the results of our study are limited by the data that manufactures were prepared to disclose. Overall, commercial manufacturers should improve the quality and value of information presented in their supporting documentation.

Unmet clinical needs for COVID-19 tests in UK health and social care settings

There is an urgent requirement to identify which clinical settings are in most need of COVID-19 tests and the priority role(s) for tests in these settings to accelerate the development of tests fit for purpose in health and social care across the UK. This study sought to identify and prioritize unmet clinical needs for COVID-19 tests across different settings within the UK health and social care sector via an online survey of health and social care professionals and policymakers. Four hundred and forty-seven responses were received between 22nd May and 15th June 2020. Hospitals and care homes were recognized as the settings with the greatest unmet clinical need for COVID-19 diagnostics, despite reporting more access to laboratory molecular testing than other settings. Hospital staff identified a need for diagnostic tests for symptomatic workers and patients. In contrast, care home staff expressed an urgency for screening at the front door to protect high-risk residents and limit transmission. The length of time to test result was considered a widespread problem with current testing across all settings. Rapid tests for staff were regarded as an area of need across general practice and dental settings alongside tests to limit antibiotics use.