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CNS disorders are lagging behind other indications in implementing genotype-dependent treatment algorithms for personalized medicine. This report uses a biophysically realistic computer model of an associative and dorsal motor cortico-striatal-thalamo-cortical loop and a working memory cortical model to investigate the pharmacodynamic effects of COMTVal158Met rs4680, 5-HTTLPR rs 25531 s/L and D2DRTaq1A1 genotypes on the clinical response of 7 antipsychotics. The effect of the genotypes on dopamine and serotonin dynamics and the level of target exposure for the drugs was calibrated from PET displacement studies. The simulations suggest strong gene-gene pharmacodynamic interactions unique to each antipsychotic. For PANSS Total, the D2DRTaq1 allele has the biggest impact, followed by the 5-HTTLPR rs25531. The A2A2 genotype improved efficacy for all drugs, with a more complex outcome for the 5-HTTLPR rs25531 genotype. Maximal range in PANSS Total for all 27 individual combinations is 3 (aripiprazole) to 5 points (clozapine). The 5-HTTLPR L/L with aripiprazole and risperidone and the D2DRTaq1A2A2 allele with haloperidol, clozapine and quetiapine reduce the motor side-effects with opposite effects for the s/s genotype. The COMT genotype has a limited effect on antipsychotic effect and EPS. For cognition, the COMT MM 5-HTTLPR L/L genotype combination has the best performance for all antipsychotics, except clozapine. Maximal difference is 25% of the total dynamic range in a 2-back working memory task. Aripiprazole is the medication that is best suited for the largest number of genotype combinations (10) followed by Clozapine and risperidone (6), haloperidol and olanzapine (3) and quetiapine and paliperidone for one genotype. In principle, the platform could identify the best antipsychotic treatment balancing efficacy and side-effects for a specific individual genotype. Once the predictions of this platform are validated in a clinical setting the platform has potential to support rational personalized treatment guidance in clinical practice.

Abstract Background Despite a tremendous amount of information on the role of amyloid in Alzheimer’s disease (AD), almost all clinical trials testing this hypothesis have failed to generate clinically relevant cognitive effects. Methods We present an advanced mechanism-based and biophysically realistic quantitative systems pharmacology computer model of an Alzheimer-type neuronal cortical network that has been calibrated with Alzheimer Disease Assessment Scale, cognitive subscale (ADAS-Cog) readouts from historical clinical trials and simulated the differential impact of amyloid-beta (Aβ40 and Aβ42) oligomers on glutamate and nicotinic neurotransmission. Results Preclinical data suggest a beneficial effect of shorter Aβ forms within a limited dose range. Such a beneficial effect of Aβ40 on glutamate neurotransmission in human patients is absolutely necessary to reproduce clinical data on the ADAS-Cog in minimal cognitive impairment (MCI) patients with and without amyloid load, the effect of APOE genotype effect on the slope of the cognitive trajectory over time in placebo AD patients and higher sensitivity to cholinergic manipulation with scopolamine associated with higher Aβ in MCI subjects. We further derive a relationship between units of Aβ load in our model and the standard uptake value ratio from amyloid imaging. When introducing the documented clinical pharmacodynamic effects on Aβ levels for various amyloid-related clinical interventions in patients with low Aβ baseline, the platform predicts an overall significant worsening for passive vaccination with solanezumab, beta-secretase inhibitor verubecestat and gamma-secretase inhibitor semagacestat. In contrast, all three interventions improved cognition in subjects with moderate to high baseline Aβ levels, with verubecestat anticipated to have the greatest effect (around ADAS-Cog value 1.5 points), solanezumab the lowest (0.8 ADAS-Cog value points) and semagacestat in between. This could explain the success of many amyloid interventions in transgene animals with an artificial high level of Aβ, but not in AD patients with a large variability of amyloid loads. Conclusions If these predictions are confirmed in post-hoc analyses of failed clinical amyloid-modulating trials, one should question the rationale behind testing these interventions in early and prodromal subjects with low or zero amyloid load.

Athan Spiros1, Robert Carr1, Hugo Geerts1,21In Silico Biosciences, Berwyn, PA, USA; 2School of Medicine, University of Pennsylvania, PA, USAAbstract: Species differences in physiology and unique active human metabolites contribute to the limited predictive value of preclinical rodent models for many central nervous system (CNS) drugs. In order to explore possible drivers for this translational disconnect, we developed a computer model of a dopaminergic synapse that simulates the competition among three agents and their binding to pre- and postsynaptic receptors, based on the affinities for their targets and their actual concentrations. The model includes presynaptic autoreceptor effects on neurotransmitter release and modulation by presynaptic firing frequency and is calibrated with actual experimental data on free dopamine levels in the striatum of the rodent and the primate. Using this model, we simulated the postsynaptic dopamine D2 receptor activation levels of bifeprunox and aripiprazole, two relatively similar dopamine D2 receptor agonists. The results indicate a substantial difference in dose–response for the two compounds when applying primate calibration parameters as opposed to rodent calibration parameters. In addition, when introducing the major human and rodent metabolites of aripiprazole with their specific pharmacological activities, the model predicts that while bifeprunox would result in a higher postsynaptic D2 receptor antagonism in the rodent, aripiprazole would result in a higher D2 receptor antagonism in the primate model. Furthermore, only the highest dose of aripiprazole, but not bifeprunox, reaches postsynaptic functional D2 receptor antagonism similar to 4 mg haloperidol in the primate model. The model further identifies a limited optimal window of functionality for dopamine D2 receptor partial agonists. These results suggest that computer modeling of key CNS processes, using well-validated calibration paradigms, can increase the predictive value in the clinical setting of preclinical animal model outcomes.Keywords: dopamine antagonism, partial agonist, antipsychotics, computer simulation

The tremendous advances in understanding the neurobiological circuits involved in schizophrenia have not translated into more effective treatments. An alternative strategy is to use a recently published 'Quantitative Systems Pharmacology' computer-based mechanistic disease model of cortical/subcortical and striatal circuits based upon preclinical physiology, human pathology and pharmacology. The physiology of 27 relevant dopamine, serotonin, acetylcholine, norepinephrine, gamma-aminobutyric acid (GABA) and glutamate-mediated targets is calibrated using retrospective clinical data on 24 different antipsychotics. The model was challenged to predict quantitatively the clinical outcome in a blinded fashion of two experimental antipsychotic drugs; JNJ37822681, a highly selective low-affinity dopamine D(2) antagonist and ocaperidone, a very high affinity dopamine D(2) antagonist, using only pharmacology and human positron emission tomography (PET) imaging data. The model correctly predicted the lower performance of JNJ37822681 on the positive and negative syndrome scale (PANSS) total score and the higher extra-pyramidal symptom (EPS) liability compared to olanzapine and the relative performance of ocaperidone against olanzapine, but did not predict the absolute PANSS total score outcome and EPS liability for ocaperidone, possibly due to placebo responses and EPS assessment methods. Because of its virtual nature, this modeling approach can support central nervous system research and development by accounting for unique human drug properties, such as human metabolites, exposure, genotypes and off-target effects and can be a helpful tool for drug discovery and development.

Objectives: Effective healthcare planning, resource allocation, and budgeting require accurate predictions of the number of patients needing treatment at specific cancer stages and treatment lines. The Predicting the Population Health Economic Impact of Current and New Cancer Treatments (PRIMCAT) for Colorectal Cancer (CRC) simulation model (PRIMCAT-CRC) was developed to meet this requirement for all CRC stages and relevant molecular profiles in Australia., Methods: Real-world data were used to estimate treatment utilization and time-to-event distributions. This populated a discrete-event simulation, projecting the number of patients receiving treatment across all disease stages and treatment lines for CRC and forecasting the number of patients likely to utilize future treatments. Illustrative analyses were undertaken, estimating treatments across disease stages and treatment lines over a 5-year period (2022-2026). We demonstrated the model's applicability through a case study introducing pembrolizumab as a first-line treatment for mismatch-repair-deficient stage IV., Results: Clinical registry data from 7163 patients informed the model. The model forecasts 15 738 incident and 2821 prevalent cases requiring treatment in 2022, rising to 15 921 and 2871, respectively, by 2026. Projections show that over 2022 to 2026, there will be a total of 116 752 treatments initiated, with 43% intended for stage IV disease. The introduction of pembrolizumab is projected for 706 patients annually, totaling 3530 individuals starting treatment with pembrolizumab over the forecasted period, without significantly altering downstream utilization of subsequent treatments., Conclusions: PRIMCAT-CRC is a versatile tool that can be used to estimate the eligible patient populations for novel cancer therapies, thereby reducing uncertainty for policymakers in decisions to publicly reimburse new treatments., Competing Interests: Author Disclosures Author disclosure forms can be accessed below in the Supplemental Material., (Copyright © 2024. Published by Elsevier Inc.)

Background: Advanced cancer significantly impacts patients' and family caregivers' quality of life. When patients and caregivers are supported concurrently as a dyad, the well-being of each person is optimized. Family, Outlook, Communication, Uncertainty, Symptom management (FOCUS) is a dyadic, psychoeducational intervention developed in the United States, shown to improve the well-being and quality of life of patients with advanced cancer and their primary caregivers. Originally, a nurse-delivered in-person intervention, FOCUS has been adapted into a self-administered web-based intervention for European delivery., Objective: The aims of this study are to (1) adapt FOCUS to the Australian context (FOCUSau); (2) evaluate the effectiveness of FOCUSau in improving the emotional well-being and self-efficacy of patients with advanced cancer and their primary caregiver relative to usual care control group; (3) compare health care use between the intervention and control groups; and (4) assess the acceptability, feasibility, and scalability of FOCUSau in order to inform future maintainable implementation of the intervention within the Australian health care system., Methods: FOCUS will be adapted prior to trial commencement, using an iterative stakeholder feedback process to create FOCUSau. To examine the efficacy and cost-effectiveness of FOCUSau and assess its acceptability, feasibility, and scalability, we will undertake a hybrid type 1 implementation study consisting of a phase 3 (clinical effectiveness) trial along with an observational implementation study. Participants will include patients with cancer who are older than 18 years, able to access the internet, and able to identify a primary support person or caregiver who can also be approached for participation. The sample size consists of 173 dyads in each arm (ie, 346 dyads in total). Patient-caregiver dyad data will be collected at 3 time points-baseline (T 0 ) completed prerandomization; first follow-up (T 1 ; N=346) at 12 weeks post baseline; and second follow-up (T 2 ) at 24 weeks post baseline., Results: The study was funded in March 2022. Recruitment commenced in July 2024., Conclusions: If shown to be effective, this intervention will improve the well-being of patients with advanced cancer and their family caregivers, regardless of their location or current level of health care support., Trial Registration: ClinicalTrials.gov NCT06082128; https://clinicaltrials.gov/study/NCT06082128., International Registered Report Identifier (irrid): PRR1-10.2196/55252., (©Peter Hudson, Jill Francis, Joachim Cohen, Suzanne Kapp, Richard De Abreu Lourenco, Lisa Beatty, Kathleen Gray, Michael Jefford, Ilona Juraskova, Laurel Northouse, Aline de Vleminck, Sungwon Chang, Patsy Yates, Sophy Athan, Shaira Baptista, Marlena Klaic, Jennifer Philip. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 13.08.2024.)

Background: Horizon scanning (HS) is the systematic identification of emerging therapies to inform policy and decision-makers. We developed an agile and tailored HS methodology that combined multi-criteria decision analysis weighting and Delphi rounds. As secondary objectives, we aimed to identify new medicines in melanoma, non-small cell lung cancer and colorectal cancer most likely to impact the Australian government's pharmaceutical budget by 2025 and to compare clinician and consumer priorities in cancer medicine reimbursement., Method: Three cancer-specific clinician panels (total n = 27) and a consumer panel (n = 7) were formed. Six prioritisation criteria were developed with consumer input. Criteria weightings were elicited using the Analytic Hierarchy Process (AHP). Candidate medicines were identified and filtered from a primary database and validated against secondary and tertiary sources. Clinician panels participated in a three-round Delphi survey to identify and score the top five medicines in each cancer type., Results: The AHP and Delphi process was completed in eight weeks. Prioritisation criteria focused on toxicity, quality of life (QoL), cost savings, strength of evidence, survival, and unmet need. In both curative and non-curative settings, consumers prioritised toxicity and QoL over survival gains, whereas clinicians prioritised survival. HS results project the ongoing prevalence of high-cost medicines. Since completion in October 2021, the HS has identified 70 % of relevant medicines submitted for Pharmaceutical Benefit Advisory Committee assessment and 60% of the medicines that received a positive recommendation., Conclusion: Tested in the Australian context, our method appears to be an efficient and flexible approach to HS that can be tailored to address specific disease types by using elicited weights to prioritise according to incremental value from both a consumer and clinical perspective., Policy Summary: Since HS is of global interest, our example provides a reproducible blueprint for adaptation to other healthcare settings that integrates consumer input and priorities., Competing Interests: Declaration of Competing Interest MA has received financial support to attend conferences and meetings by AstraZeneca and serves on the advisory board for Pfizer and Bristol Myers Squibb. PAA has/had a consultant/advisory role for Bristol Myers Squibb, Roche-Genentech, Merck Sharp & Dohme, Novartis, Merck Serono, Pierre-Fabre, AstraZeneca, Sun Pharma, Canofi, Idera, Sandoz, Immunocore, 4SC, Italfarmaco, Nektar, Boehringer-Ingelheim, Eisai, Regeneron, Daiichi Sankyo, Pfizer, Oncosec, Nouscom, Lunaphore, Seagen, iTeos, Medicenna, Bio-Al Health, ValoTX, Replimmune. He has received research funding grants from Bristol Myers Squibb, Roche-Genentech, Pfizer, Sanofi. He has received travel support from Pfizer. SA has served uncompensated on the boards of Health Issues Centre, Australia, Victorian Agency for Health Information, and Safer Care Victoria. MPB has received honoraria from BNS Australia, USD Oncology, and Novartis. He holds an advisory role for Bristol Myers Squibb, Merck Sharp & Dohme, Novartis, and Cartherics for which his institution receives reimbursements. His institution has also received reimbursement for research support from Bristol Myers Squibb, Merck Sharp & Dohme, Pharmaust, Zucero Therapeutics, and CStone Pharmaceuticals. MB has received compensation and research support as an advisor and consultant to Pierre Fabre, MSD, GSK, Servier, and AstraZeneca. MI is on the advisory boards of Pfizer, Roche, Takeda, BeiGene, Amgen, Merck, and MSD and has received honoraria from Pfizer, Roche, Takeda, Novartis, as well as research funding from Pfizer. TJ reports consulting fees from AstraZeneca and MSD, and advisory boards and committees for AstraZeneca, Amgen, Bristol Myers Squibb, Merck & Co., MSD, Gilead, Puma, Pfizer Inc., Roche AG, Specialised Therapeutics, and Takeda Pharmaceutical, outside the submitted work. SK reports honoraria to institution from Astra Zeneca, Roche, Pfizer, Bristol Myers Squibb, MSD and Takeda; consulting fees from AstraZeneca, Pfizer, MSD, Novartis, Roche, Takeda, Amgen; and research funding to institution from Astra Zeneca. MK reports institutional grants from Nordic Farma, Merck-Serono, Pierre Fabre, Servier, Bayer, Bristol Myers Squibb, Merck, and Roche; and consulting fees and honoraria paid to institution from Pierre Fabre and Servier. BTL has served as an uncompensated advisor and consultant to Amgen, AstraZeneca, Boehringer Ingelheim, Bolt Biotherapeutics, Daiichi Sankyo, Genentech, and Lilly. He has received research grants to his institution from Amgen, AstraZeneca, Bolt Biotherapeutics, Daiichi Sankyo, Genentech, Hengrui USA, and Lilly. He has received academic travel support from Amgen, Jiangsu Hengrui Medicine and MORE Health. He is an inventor on two institutional patents at MSK (US62/685,057, US62/514,661) and has intellectual property rights as a book author at Karger Publishers and Shanghai Jiao Tong University Press. BTL is supported by the Memorial Sloan Kettering Cancer Centre Support Grant P30 CA008748 and Research Project Grant R01CA249666 from the National Institutes of Health. GVL is consultant advisor for Agenus, Amgen, Array Biopharma, AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, Evaxion, Hexal AG (Sandoz Company), Highlight Therapeutics S.L., Innovent Biologics USA, Merck Sharpe & Dohme, Novartis, OncoSec, PHMR Ltd, Pierre Fabre, Provectus, Qbiotics, Regeneron. JML receives research support from Ipsen Pharmaceuticals, Novartis and Amgen, and reports consulting fees and/or honoraria from Amgen, Ipsen, Taiho, Novartis, SAGA Diagnostics and Natera. BM is on the advisory boards of Amgen, MSD, Bristol Myers Squibb, Beigene and AstraZeneca. GAM has received research support from Bristol Myers Squibb and as Principal Investigator his institution has received reimbursement of trial costs from Roche-Genentech. TMM reports consulting fees and participation on advisory boards for Bristol Myers Squibb, MSD, Merck, AstraZeneca, Novartis, GSK, Eisai, and honoraria from AstraZeneca. TMM has received support to attend meetings from Bristol Myers Squibb and AstraZeneca. LN has received institutional consulting fees from Bristol Myers Squibb, Pfizer, and Merck Sharp & Dohme, and reports support to attend a research meeting from AstraZeneca. NP has served on advisory boards or received personal honoraria from Boehringer Ingelheim, MSD, Merck, Bristol-Myers Squib, Astra Zeneca, Takeda, Pfizer, Roche, Novartis, Ipsen and Bayer and has received research funding to his institution from Bayer, Pfizer and Roche. TMP has received research support from Roche and Pfizer, and holds a consulting or advisory role for Merck, Bristol Myers Squibb, Novartis, Sanofi/Regeneron, and Pfizer. SP is compensated consultant to Amgen, AstraZeneca, Bayer, Blueprint, BMS, Boehringer Ingelheim, Daiichi Sankyo, EQRx, GSK, Guardant Health, Incyte, Janssen, Lilly, Merck Serono, MSD, Novartis, Roche, Takeda, Pfizer, Seattle Genetics, Turning Point Therapeutics, declares expert testimony to Roche and Merck Serono, and travel support from Janssen and Roche.BJS is on the Advisory Boards/Honoraria for Pfizer, Novartis, Roche, AstraZeneca, Merck, Bristol Myers Squibb, Eli Lilly, Amgen, BeiGene, Janssen, Takeda. JAS has received support for conference attendance from MSD (virtual registration ASCO). JT has received consulting fees or honoraria from Haystack Oncology, Servier, Pierre Fabre, MSD, Merck Serono, Amgen, Novartis, Seres and AstraZeneca. JT is on the advisory boards of Beigene, Daiichi Sankyo, Gilead, Illumina, Novartis, BMS, and MSD. WX has received research support from Merck, honoraria from MSD, Merck and AstraZeneca, and support for attending meetings from MSD (virtual registration ASCO) and Eli Lilly (virtual registration SABCS). WX is on the advisory boards of MSD, Merck and Novartis, and holds unpaid positions as Chair of the Melanoma and Skin Cancer trials group and Australasian Merkel Cell Carcinoma interest group.DY has received institutional payments for his role on advisory boards for AstraZeneca, Servier, Specialised Therapeutics, MSD and BayerJZ serves in an advisory/consultancy role for Merck Sharp & Dohme, Specialised Therapeutics, CEND, Deciphera, Revolution Medicine, FivePHusion, Genorbio, 1Global, Novotech, Alloplex Biotherapeutics, NOUS Consulting, and Oncology Republic; owns stock in Biomarin, Ophthea, Amarin, Concert Pharmaceuticals, Frequency Therapeutics, Gilead, Madrigal Pharmaceuticals, UniQure, Zogenix, Orphazyme, Moderna Therapeutics, TWST, Novavax, and Teladoc; has received honoraria from Gilead Sciences, MSD Oncology, and Viatris; and his institution has received research funding from Bristol-Myers Squibb, AstraZeneca, Pfizer, IQvia, Mylan, Ipsen, Eisai, Medtronic, MSD Oncology and Servier; and has received travel, accommodations, expenses from ICON Group, MSD Oncology, and PRAXIS., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Increasing awareness of the importance of pathology stewardship in reducing low value care has led to scrutiny of appropriate laboratory test ordering. The objective of this study is to investigate the value of a commonly ordered laboratory test, the C-reactive protein (CRP), in decisions regarding diagnosis, management and disposition of emergency department (ED) patients with suspected sepsis. Retrospective chart reviews were performed on 1716 adult patients with suspected sepsis presenting to the Townsville University Hospital ED between 1 January 2021 and 30 June 2021. Suspected sepsis was defined as the emergency clinicians' decision to perform a blood culture. A CRP value of 10 mg/L or higher was defined as an elevated CRP. The primary outcome of interest was commencement of antibiotics in ED. Secondary outcomes include hospital admission (ward and ICU), hospital length of stay, mortality, documentation of indication for CRP testing, test parameters of CRP in detecting culture-positive bacteraemia and rates of bacteraemia with presumptive ED diagnosis. This study found no significant association between CRP values and antibiotic commencement (p=0.222), ward admission (p=0.071), ICU admission (p=0.248), hospital length of stay (p=0.164) or mortality (p=1.000). CRP had an area under the curve of 0.58 (95% CI 0.51-0.66) for detecting culture-positive bacteraemia. Sensitivity and specificity of CRP were 62.5% and 47.7%, respectively, at a threshold of 46 mg/dL. CRP testing is of little value in ED patients with suspected sepsis as it does not influence decision making about diagnosis, management, or disposition. Avoiding CRP testing in this patient cohort can contribute to pathology stewardship and optimal use of finite healthcare resources., (Crown Copyright © 2023. Published by Elsevier B.V. All rights reserved.)