Therapeutic innovation to address sickle cell disease (SCD) is at a historical apex, characterized by a drug discovery, development, and commercialization landscape that includes potentially curative gene therapies. Given the wide geographic distribution of SCD, with a major presence in Africa, it is imperative that new medicines are designed to meet the specific needs of persons with SCD everywhere. Target product profiles (TPPs) detail the desired attributes of new medicines and serve as a guide for drug developers. To support research efforts for curative treatments for SCD, we mobilized a large multi-disciplinary expert group to generate consensus-driven TPPs for ex vivo and in vivo SCD gene therapies, utilizing a modified Delphi methodology supplemented with virtual workshops. The main findings are TPPs that describe 20 minimal and optimal criteria for novel gene therapy products in categories of scope (3 criteria), performance/safety (11 criteria), manufacturing (4 criteria), and administration (2 criteria). TPPs for ex vivo and in vivo products differed in some performance/safety criteria and all criteria pertaining to manufacturing and administration. These outputs will ideally support development of durable treatments that are safe, efficacious, and practical for persons with SCD in global settings.

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.
CONCLUSIONS: 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.

Diagnostic tests were heralded as crucial during the Coronavirus disease (COVID-19) pandemic with most of the key methods using bioanalytical approaches that detected larger molecules (RNA, protein antigens or antibodies) rather than conventional clinical biochemical techniques. Nucleic Acid Amplification Tests (NAATs), like the Polymerase Chain Reaction (PCR), and other molecular methods, like sequencing (that often work in combination with NAATs), were essential to the diagnosis and management during COVID-19. This was exemplified both early in the pandemic but also later on, following the emergence of new genetic SARS-CoV-2 variants. The 100 day mission to respond to future pandemic threats highlights the need for effective diagnostics, therapeutics and vaccines. Of the three, diagnostics represents the first opportunity to manage infectious diseases while also being the most poorly supported in terms of the infrastructure needed to demonstrate effectiveness. Where performance targets exist, they are not well served by consensus on how to demonstrate they are being met; this includes analytical factors such as limit of detection (LOD) false positive results as well as how to approach clinical evaluation. The selection of gold standards or use of epidemiological factors such as predictive value, reference ranges or clinical thresholds are seldom correctly considered. The attention placed on molecular diagnostic tests during COVID-19 illustrates important considerations and assumptions on the use of these methods for infectious disease diagnosis and beyond. In this manuscript, we discuss state-of-the-art approaches to diagnostic evaluation and explore how they may be better tailored to diagnostic techniques like NAATs to maximise the impact of these highly versatile bioanalytical tools, both generally and during future outbreaks.

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.
UNASSIGNED: DERR1-10.2196/50568.

Matching crop varieties to their target use context and user preferences is a challenge faced by many plant breeding programs serving smallholder agriculture. Numerous participatory approaches proposed by CGIAR and other research teams over the last four decades have attempted to capture farmers\' priorities/preferences and crop variety field performance in representative growing environments through experimental trials with higher external validity. Yet none have overcome the challenges of scalability, data validity and reliability, and difficulties in capturing socio-economic and environmental heterogeneity. Building on the strengths of these attempts, we developed a new data-generation approach, called triadic comparison of technology options (tricot). Tricot is a decentralized experimental approach supported by crowdsourced citizen science. In this article, we review the development, validation, and evolution of the tricot approach, through our own research results and reviewing the literature in which tricot approaches have been successfully applied. The first results indicated that tricot-aggregated farmer-led assessments contained information with adequate validity and that reliability could be achieved with a large sample. Costs were lower than current participatory approaches. Scaling the tricot approach into a large on-farm testing network successfully registered specific climatic effects of crop variety performance in representative growing environments. Tricot\'s recent application in plant breeding networks in relation to decision-making has (i) advanced plant breeding lines recognizing socio-economic heterogeneity, and (ii) identified consumers\' preferences and market demands, generating alternative breeding design priorities. We review lessons learned from tricot applications that have enabled a large scaling effort, which should lead to stronger decision-making in crop improvement and increased use of improved varieties in smallholder agriculture.

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.
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.
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).
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.

Therapeutic biology encompasses different modalities, and their manufacturing processes may be vastly different. However, there are many similarities that run across the different modalities during the drug product (DP) development process and manufacturing. Similarities include the need for Quality Target Product Profile (QTTP), analytical development, formulation development, container/closure studies, drug product process development, manufacturing and technical requirements set out by numerous regulatory documents such as the FDA, EMA, and ICH for pharmaceuticals for human use and other country specific requirements. While there is a plethora of knowledge on studies needed for development of a drug product, there is no specific guidance set out in a phase dependent manner delineating what studies should be completed in alignment with the different phases of clinical development from pre-clinical through commercialization. Because of this reason, we assembled a high-level drug product development and manufacturing roadmap. The roadmap is applicable across the different modalities with the intention of providing a unified framework from early phase development to commercialization of biologic drug products.

While progress has been made in the development of islet cell transplantation (ICT) as a viable alternative to the use of exogenous insulin therapy in the treatment of type 1 diabetes, it has not yet achieved its full potential in clinical studies. Ideally, ICT would enable lifelong maintenance of euglycemia without the need for exogenous insulin, blood glucose monitoring or systemic immune suppression. To achieve such an optimal result, therapeutic approaches should simultaneously promote long-term islet viability, functionality, and localized immune protection. In practice, however, these factors are typically tackled individually. Furthermore, while the requirements of optimal ICT are implicitly acknowledged across numerous publications, the literature contains few comprehensive articulations of the target product profile (TPP) for an optimal ICT product, including key characteristics of safety and efficacy. This review aims to provide a novel TPP for ICT and presents promising tried and untried combinatorial approaches that could be used to achieve the target product profile. We also highlight regulatory barriers to the development and adoption of ICT, particularly in the United States, where ICT is only approved for use in academic clinical trials and is not reimbursed by insurance carriers. Overall, this review argues that the clear definition of a TPP in addition to the use of combinatorial approaches could help to overcome the clinical barriers to the widespread adoption of ICT for the treatment of type 1 diabetes.

Elimination of mother-to-child transmission of hepatitis B virus (HBV) requires infant immunoprophylaxis and antiviral prophylaxis for pregnant women with high viral loads. Since real-time polymerase chain reaction (RT-PCR), a gold standard for assessing antiviral eligibility, is neither accessible nor affordable for women living in low-income and middle-income countries (LMICs), rapid diagnostic tests (RDTs) detecting alternative HBV markers may be needed. To inform future development of the target product profile (TPP) for RDTs to identify highly viremic women, we used a discrete choice experiment (DCE) and elicited preference and trade-off of healthcare workers (HCW) in Africa between the following four attributes of fictional RDTs: price, time-to-result, diagnostic sensitivity, and specificity.
Through an online questionnaire survey, we asked participants to indicate their preferred test from a set of two RDTs in seven choice tasks with varying levels of the four attributes. We used mixed multinomial logit models to quantify the utility gain or loss generated by each attribute. We attempted to define minimal and optimal criteria for test attributes that can satisfy ≥ 70% and ≥ 90% of HCWs, respectively, as an alternative to RT-PCR.
A total of 555 HCWs from 41 African countries participated. Increases in sensitivity and specificity generated significant utility and increases in cost and time-to-result generated significant disutility. The size of the coefficients for the highest attribute levels relative to the reference levels were in the following order: sensitivity (β = 3.749), cost (β = -2.550), specificity (β = 1.134), and time-to-result (β = -0.284). Doctors cared most about test sensitivity, while public health practitioners cared about cost and midwives about time-to-result. For an RDT with 95% specificity, costing 1 US$, and yielding results in 20 min, the minimally acceptable test sensitivity would be 82.5% and the optimally acceptable sensitivity would be 87.5%.
African HCWs would prefer an RDT with the following order of priority: higher sensitivity, lower cost, higher specificity, and shorter time-to-result. The development and optimization of RDTs that can meet the criteria are urgently needed to scale up the prevention of HBV mother-to-child transmission in LMICs.

In September 2022, the Drug Discovery Unit at the University of Dundee, UK, organised an international meeting at the Wellcome Collection in London to explore the current clinical situation and challenges associated with treating schistosomiasis. The aim of this meeting was to discuss the need for new treatments in view of the clinical situation and to ascertain what the key requirements would be for any potential new anti-schistosomals. This information will be essential to inform ongoing drug discovery efforts for schistosomiasis. We also discussed the potential drug discovery pathway and associated criteria for progressing compounds to the clinic. To date, praziquantel (PZQ) is the only drug available to treat all species causing schistosomiasis, but it is often unable to completely clear parasites from an infected patient, partially due to its inactivity against juvenile worms. PZQ-mediated mass drug administration campaigns conducted in endemic areas (e.g., sub-Saharan Africa, where schistosomiasis is primarily prevalent) have contributed to reducing the burden of disease but will not eliminate the disease as a public health problem. The potential for Schistosoma to develop resistance towards PZQ, as the sole treatment available, could become a concern. Consequently, new anthelmintic medications are urgently needed, and this Perspective aims to capture some of the learnings from our discussions on the key criteria for new treatments.