Development of a target product profile for a point-of-care cardiometabolic device

Introduction Multi-parameter diagnostic devices can simplify cardiometabolic disease diagnosis. However, existing devices may not be suitable for use in low-resource settings, where the burden of non-communicable diseases is high. Here we describe the development of a target product profile (TPP) for a point-of-care multi-parameter device for detection of biomarkers for cardiovascular disease and metabolic disorders, including diabetes, in primary care settings in low- and middle-income countries (LMICs). Methods A draft TPP developed by an expert group was reviewed through an online survey and semi-structured expert interviews to identify device characteristics requiring refinement. The draft TPP included 41 characteristics with minimal and optimal requirements; characteristics with an agreement level for either requirement of ≤ 85% in either the survey or among interviewees were further discussed by the expert group and amended as appropriate. Results Twenty people responded to the online survey and 18 experts participated in the interviews. Twenty-two characteristics had an agreement level of ≤ 85% in either the online survey or interviews. The final TPP defines the device as intended to be used for basic diagnosis and management of cardiometabolic disorders (lipids, glucose, HbA1c, and creatinine) as minimal requirement, and offering an expanded test menu for wider cardiometabolic disease management as optimal requirement. To be suitable, the device should be intended for level 1 healthcare settings or lower, used by minimally trained healthcare workers and allow testing using self-contained cartridges or strips without the need for additional reagents. Throughput should be one sample at a time in a single or multi-analyte cartridge, or optimally enable testing of several samples and analytes in parallel with random access. Conclusion This TPP will inform developers of cardiometabolic multi-parameter devices for LMIC settings, and will support decision makers in the evaluation of existing and future devices.

Development and implementation of an enterprise-wide predictive model for early absorption, distribution, metabolism and excretion properties

Background: Accurate prediction of absorption, distribution, metabolism and excretion (ADME) properties can facilitate the identification of promising drug candidates. Methodology & Results: The authors present the Janssen generic Target Product Profile (gTPP) model, which predicts 18 early ADME properties, employs a graph convolutional neural network algorithm and was trained on between 1000–10,000 internal data points per predicted parameter. gTPP demonstrated stronger predictive power than pretrained commercial ADME models and automatic model builders. Through a novel logging method, the authors report gTPP usage for more than 200 Janssen drug discovery scientists. Conclusion: The investigators successfully enabled the rapid and systematic implementation of predictive ML tools across a drug discovery pipeline in all therapeutic areas. This experience provides useful guidance for other large-scale AI/ML deployment efforts.

Target product profile for a dengue pre-vaccination screening test

With increasing geographic spread, frequency, and magnitude of outbreaks, dengue continues to pose a major public health threat worldwide. Dengvaxia, a dengue live-attenuated tetravalent vaccine, was licensed in 2015, but post hoc analyses of long-term data showed serostatus-dependent vaccine performance with an excess risk of hospitalized and severe dengue in seronegative vaccine recipients. The World Health Organization (WHO) recommended that only persons with evidence of past dengue infection should receive the vaccine. A test for pre-vaccination screening for dengue serostatus is needed. To develop the target product profile (TPP) for a dengue pre-vaccination screening test, face-to-face consultative meetings were organized with follow-up regional consultations. A technical working group was formed to develop consensus on a reference test against which candidate pre-vaccination screening tests could be compared. The group also reviewed current diagnostic landscape and the need to accelerate the evaluation, regulatory approval, and policy development of tests that can identify seropositive individuals and maximize public health impact of vaccination while avoiding the risk of hospitalization in dengue-naive individuals. Pre-vaccination screening strategies will benefit from rapid diagnostic tests (RDTs) that are affordable, sensitive, and specific and can be used at the point of care (POC). The TPP described the minimum and ideal characteristics of a dengue pre-vaccination screening RDT with an emphasis on high specificity. The group also made suggestions for accelerating access to these RDTs through streamlining regulatory approval and policy development. Risk and benefit based on what can be achieved with RDTs meeting minimal and optimal characteristics in the TPP across a range of seroprevalences were defined. The final choice of RDTs in each country will depend on the performance of the RDT, dengue seroprevalence in the target population, tolerance of risk, and cost-effectiveness.

Prospective validation of host transcriptomic biomarkers for pulmonary tuberculosis by real-time PCR

We tested performance of host-blood transcriptomic tuberculosis (TB) signatures for active case-finding. Among 20,207 HIV-uninfected and 963 HIV-infected adults screened; 2,923 and 861 were enrolled from five South African communities. Eight signatures were measured by microfluidic RT-qPCR and participants were microbiologically-investigated for pulmonary TB at baseline, and actively surveilled for incident disease through 15 months. Diagnostic AUCs for 61 HIV-uninfected (weighted-prevalence 1.1%) and 10 HIV-infected (prevalence 1.2%) prevalent TB cases for the 8 signatures were 0.63-0.79 and 0.65-0.88, respectively. Thereafter, 24 HIV-uninfected and 9 HIV-infected participants progressed to incident TB (1.1 and 1.0 per 100 person-years, respectively). Prognostic AUCs through 15-months follow-up were 0.49-0.66 and 0.54-0.81, respectively. Prognostic performance for incident TB occurring within 6-12 months in HIV-negative participants was higher for all signatures. None of the signatures met WHO Target Product Profile criteria for a triage test to diagnose asymptomatic TB; most signatures met the criteria for symptomatic TB. Prognostic accuracy of most signatures for incident TB within six months of testing met the criteria for an incipient TB test.

SERCAP: is the perfect the enemy of the good?

Single Encounter Radical Cure and Prophylaxis (SERCAP) describes an ideal anti-malarial drug that cures all malaria in a single dose. This target product profile has dominated anti-malarial drug discovery and development over the past decade. The operational advantage of a single encounter has to be balanced against the need for a high dose, reliable absorption, little variability in pharmacokinetic properties, slow elimination (to ensure curative drug exposures in all patients) and a very low rate of vomiting. The demanding aspirational target may have hindered anti-malarial drug development. Aiming for three-day regimens, as in current anti-malarial treatments, would be better.

Lean Six Sigma untuk Mengurangi Waste Pada Produksi Tablet Coating A

PT. Medica Indonesia salah satu perusahaan farmasi etikal terbesar di Indonesia. Departement Pilot Plant berperan sebagai fasilitas peningkatan skala setelah skala lab untuk memastikan bahwa QTPP (Quality Target Product Profile) secara konsisten dicapai dalam skala pilot dan skala produksi. Masih tingginya angka reject sebesar 3,6 % dari target reject sebesar 0,5 % pada produk andalan tablet coating A merupakan suatu ancaman. Identifikasi penyebab pemborosan perlu dilakukan untuk peningkatan dan perbaikan pada lini produksi. Penelitian ini melakukan Integrasi Lean Six Sigma dengan menggunakan metode DMAIC, VSM dan VALSAT. Analisa menggunakan tools WRM dan WAQ. Berdasarkan Analisa VALSAT, ditemukan 3 pemborosan terbesar yaitu defect (38,47%), overproduction (16,32%) dan inventory (10,13%). Pemborosan diidentifikasi menggunakan diagram fishbone kemudian dari analisis FMEA menunjukan nilai RPN tertinggi yang dijadikan prioritas usulan perbaikan. Hasil menunjukan pengurangan defect ratio dari 10,35 % menjadi 1,65 % dan pengurangan waste inventory yang diakibatkan overproduction.

Target Product Profile Analysis of COVID-19 Vaccines in Phase III Clinical Trials and Beyond: An Early 2021 Perspective

The coronavirus SARS-CoV-2, which causes Coronavirus disease 2019 (COVID-19), has infected more than 100 million people globally and caused over 2.5 million deaths in just over one year since its discovery in Wuhan, China in December 2019. The pandemic has evoked widespread collateral damage to societies and economies, and has destabilized mental health and well-being. Early in 2020, unprecedented efforts went into the development of vaccines that generate effective antibodies to the SARS-CoV-2 virus. Teams developing twelve candidate vaccines, based on four platforms (messenger RNA, non-replicating viral vector, protein/virus-like particle, and inactivated virus) had initiated or announced the Phase III clinical trial stage by early November 2020, with several having received emergency use authorization in less than a year. Vaccine rollout has proceeded around the globe. Previously, we and others had proposed a target product profile (TPP) for ideal/optimal and acceptable/minimal COVID-19 vaccines. How well do these candidate vaccines stack up to a harmonized TPP? Here, we perform a comparative analysis in several categories of these candidate vaccines based on the latest available trial data and highlight the early successes as well as the hurdles and barriers yet to be overcome for ending the global COVID-19 pandemic.

Modelling of hypothetical SARS-CoV-2 point-of-care tests on admission to hospital from A&E: rapid cost-effectiveness analysis

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes coronavirus disease 2019. At the time of writing (October 2020), the number of cases of COVID-19 had been approaching 38 million and more than 1 million deaths were attributable to it. SARS-CoV-2 appears to be highly transmissible and could rapidly spread in hospital wards. Objective The work undertaken aimed to estimate the clinical effectiveness and cost-effectiveness of viral detection point-of-care tests for detecting SARS-CoV-2 compared with laboratory-based tests. A further objective was to assess occupancy levels in hospital areas, such as waiting bays, before allocation to an appropriate bay. Perspective/setting The perspective was that of the UK NHS in 2020. The setting was a hypothetical hospital with an accident and emergency department. Methods An individual patient model was constructed that simulated the spread of disease and mortality within the hospital and recorded occupancy levels. Thirty-two strategies involving different hypothetical SARS-CoV-2 tests were modelled. Recently published desirable and acceptable target product profiles for SARS-CoV-2 point-of-care tests were modelled. Incremental analyses were undertaken using both incremental cost-effectiveness ratios and net monetary benefits, and key patient outcomes, such as death and intensive care unit care, caused directly by COVID-19 were recorded. Results A SARS-CoV-2 point-of-care test with a desirable target product profile appears to have a relatively small number of infections, a low occupancy level within the waiting bays, and a high net monetary benefit. However, if hospital laboratory testing can produce results in 6 hours, then the benefits of point-of-care tests may be reduced. The acceptable target product profiles performed less well and had lower net monetary benefits than both a laboratory-based test with a 24-hour turnaround time and strategies using data from currently available SARS-CoV-2 point-of-care tests. The desirable and acceptable point-of-care test target product profiles had lower requirement for patients to be in waiting bays before being allocated to an appropriate bay than laboratory-based tests, which may be of high importance in some hospitals. Tests that appeared more cost-effective also had better patient outcomes. Limitations There is considerable uncertainty in the values for key parameters within the model, although calibration was undertaken in an attempt to mitigate this. The example hospital simulated will also not match those of decision-makers deciding on the clinical effectiveness and cost-effectiveness of introducing SARS-CoV-2 point-of-care tests. Given these limitations, the results should be taken as indicative rather than definitive, particularly cost-effectiveness results when the relative cost per SARS-CoV-2 point-of-care test is uncertain. Conclusions Should a SARS-CoV-2 point-of-care test with a desirable target product profile become available, this appears promising, particularly when the reduction on the requirements for waiting bays before allocation to a SARS-CoV-2-infected bay, or a non-SARS-CoV-2-infected bay, is considered. The results produced should be informative to decision-makers who can identify the results most pertinent to their specific circumstances. Future work More accurate results could be obtained when there is more certainty on the diagnostic accuracy of, and the reduction in time to test result associated with, SARS-CoV-2 point-of-care tests, and on the impact of these tests on occupancy of waiting bays and isolation bays. These parameters are currently uncertain. Funding This report was commissioned by the National Institute for Health Research (NIHR) Evidence Synthesis programme as project number 132154. This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 21. See the NIHR Journals Library website for further project information.