TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations.

Achieving a balance between computational speed, prediction accuracy, and universal applicability in molecular simulations has been a persistent challenge. This paper presents substantial advancements in TorchMD-Net software, a pivotal step forward in the shift from conventional force fields to neural network-based potentials. The evolution of TorchMD-Net into a more comprehensive and versatile framework is highlighted, incorporating cutting-edge architectures such as TensorNet. This transformation is achieved through a modular design approach, encouraging customized applications within the scientific community. The most notable enhancement is a significant improvement in computational efficiency, achieving a very remarkable acceleration in the computation of energy and forces for TensorNet models, with performance gains ranging from 2× to 10× over previous, nonoptimized, iterations. Other enhancements include highly optimized neighbor search algorithms that support periodic boundary conditions and smooth integration with existing molecular dynamics frameworks. Additionally, the updated version introduces the capability to integrate physical priors, further enriching its application spectrum and utility in research. The software is available at https://github.com/torchmd/torchmd-net.

TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations.

Achieving a balance between computational speed, prediction accuracy, and universal applicability in molecular simulations has been a persistent challenge. This paper presents substantial advancements in the TorchMD-Net software, a pivotal step forward in the shift from conventional force fields to neural network-based potentials. The evolution of TorchMD-Net into a more comprehensive and versatile framework is highlighted, incorporating cutting-edge architectures such as TensorNet. This transformation is achieved through a modular design approach, encouraging customized applications within the scientific community. The most notable enhancement is a significant improvement in computational efficiency, achieving a very remarkable acceleration in the computation of energy and forces for TensorNet models, with performance gains ranging from 2-fold to 10-fold over previous iterations. Other enhancements include highly optimized neighbor search algorithms that support periodic boundary conditions and the smooth integration with existing molecular dynamics frameworks. Additionally, the updated version introduces the capability to integrate physical priors, further enriching its application spectrum and utility in research. The software is available at https://github.com/torchmd/torchmd-net.

OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials.

Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use of machine learning potentials. Arbitrary PyTorch models can be added to a simulation and used to compute forces and energy. A higher-level interface allows users to easily model their molecules of interest with general purpose, pretrained potential functions. A collection of optimized CUDA kernels and custom PyTorch operations greatly improves the speed of simulations. We demonstrate these features in simulations of cyclin-dependent kinase 8 (CDK8) and the green fluorescent protein chromophore in water. Taken together, these features make it practical to use machine learning to improve the accuracy of simulations with only a modest increase in cost.

OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials.

Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use of machine learning potentials. Arbitrary PyTorch models can be added to a simulation and used to compute forces and energy. A higher-level interface allows users to easily model their molecules of interest with general purpose, pretrained potential functions. A collection of optimized CUDA kernels and custom PyTorch operations greatly improves the speed of simulations. We demonstrate these features on simulations of cyclin-dependent kinase 8 (CDK8) and the green fluorescent protein (GFP) chromophore in water. Taken together, these features make it practical to use machine learning to improve the accuracy of simulations at only a modest increase in cost.

NNP/MM: Accelerating Molecular Dynamics Simulations with Machine Learning Potentials and Molecular Mechanics.

Machine learning potentials have emerged as a means to enhance the accuracy of biomolecular simulations. However, their application is constrained by the significant computational cost arising from the vast number of parameters compared with traditional molecular mechanics. To tackle this issue, we introduce an optimized implementation of the hybrid method (NNP/MM), which combines a neural network potential (NNP) and molecular mechanics (MM). This approach models a portion of the system, such as a small molecule, using NNP while employing MM for the remaining system to boost efficiency. By conducting molecular dynamics (MD) simulations on various protein-ligand complexes and metadynamics (MTD) simulations on a ligand, we showcase the capabilities of our implementation of NNP/MM. It has enabled us to increase the simulation speed by ∼5 times and achieve a combined sampling of 1 µs for each complex, marking the longest simulations ever reported for this class of simulations.

Dying at home: enablers and barriers.

BACKGROUND: According to the Grattan institute in 2014, 70% of Australians indicated a preference to die at home, however, only 14% of all deaths were at home. AIMS: To identify how patients can be supported to die at home if that is their preference. METHODS: A retrospective medical record audit of eligible Community Palliative Care (CPC) patients who indicated a wish to die at home was undertaken. FINDINGS: Out of a total of 114 patients, 74% indicated a preference to die at home. Of these, 66% achieved a home death, and most lived with a carer. Enablers for home death included family support, regular nursing visits and equipment. People who attended an emergency department in their last month of life, lived alone or were undergoing oncological treatment were more likely to die elsewhere. CONCLUSION: A range of enablers and barriers to home death were found, with many of the enablers being factors that prevented hospital presentations.

Does cancer type and adjuvant analgesic prescribing influence opioid dose?-a retrospective cross-sectional study.

Opioids are the backbone of cancer pain management. Minimal evidence exists examining the relationship between cancer type and opioid dose. Similarly, the use of adjuvant analgesics and its impact within an inpatient cancer setting is understudied. This study examined the influence of cancer type upon opioid dose, measured by oral morphine equivalent daily dose (oMEDD). The effect of adjuvant analgesics on patient oMEDD was also examined. This retrospective cross-sectional study examined records of 520 patients admitted to Royal Melbourne Hospital or Peter MacCallum Cancer Centre between 2016 and 2018 with advanced cancer. Number and dose of both opioid and adjuvant analgesics were collected along with demographic and cancer data. Comparisons of median oMEDD by cancer type [analysis of variance (ANOVA), non-parametric t-tests] and adjuvant analgesics (Kruskal-Wallis test) were performed. There were no statistically significant differences in oMEDD between the 12 cancer types (P=0.83; n=215). Patients co-prescribed pregabalin (n=102) and paracetamol (n=73) as adjuvant analgesics were on significantly higher daily oMEDD [60 mg (P=0.015), 90 mg (P<0.001), respectively]. Opioid dose did not differ significantly between cancer types. The observed use of adjuvant analgesics coincided with significantly higher oMEDD prescription which may relate to complex pain seen in this cohort of inpatients in a quarternary cancer centre. Future research should focus on pain type and aetiology, and pain scores in different cancer pain syndromes to determine the net effect of opioids and adjuvants in cancer pain prescribing.

SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials.

Machine learning potentials are an important tool for molecular simulation, but their development is held back by a shortage of high quality datasets to train them on. We describe the SPICE dataset, a new quantum chemistry dataset for training potentials relevant to simulating drug-like small molecules interacting with proteins. It contains over 1.1 million conformations for a diverse set of small molecules, dimers, dipeptides, and solvated amino acids. It includes 15 elements, charged and uncharged molecules, and a wide range of covalent and non-covalent interactions. It provides both forces and energies calculated at the ωB97M-D3(BJ)/def2-TZVPPD level of theory, along with other useful quantities such as multipole moments and bond orders. We train a set of machine learning potentials on it and demonstrate that they can achieve chemical accuracy across a broad region of chemical space. It can serve as a valuable resource for the creation of transferable, ready to use potential functions for use in molecular simulations.

Symptom burden in malignant and non-malignant disease on admission to a palliative care unit.

BACKGROUND: There is increasing recognition that patients with non-malignant diseases have comparable physical and psychosocial symptom burden to patients with cancer. There is currently limited data directly comparing symptom burden between these patient groups. OBJECTIVE: To investigate differences in symptom burden between patients with malignant and non-malignant conditions admitted to a palliative care unit (PCU). METHOD: A cross-sectional study involving 186 patients admitted to a PCU was undertaken. Patients were dichotomised into malignant or non-malignant disease categories. Symptom burden at admission was assessed using the Symptom Assessment Scale and Palliative Care Problem Severity Score. Group differences in symptoms were analysed using univariate and multivariate approaches. RESULTS: One hundred patients (53.8%) had cancer, with upper gastrointestinal the most common type (18.0%). Among the 86 patients with non-malignant disease, neurological conditions were most prevalent (40.7%). Patients admitted with non-malignant diseases were older, more functionally impaired and more likely to be deteriorating or terminal. A malignant diagnosis was associated with a higher likelihood of clinician-assessed pain, patient-assessed pain, fatigue, psychological/spiritual symptoms and other symptoms. However, when adjusted for confounders, disease category ceased to be a significant predictor of symptom burden. Younger patients experienced worse pain and patients in terminal phase experienced less symptom burden. CONCLUSION: Symptom burden was similar between patients with malignant and non-malignant disease after adjustment for confounders. Further research is needed to understand the palliative care needs of patients with non-malignant disease.

Telehealth: rapid adoption in community palliative care due to COVID-19: patient and professional evaluation.

BACKGROUND/OBJECTIVE: The COVID-19 pandemic has brought the use of telehealth to the fore, as many people have been unable to interact directly with healthcare professionals (HCP). For community palliative care (CPC) services, this has meant a sudden change from a predominantly face-to-face model of care to one that incorporates telehealth. Understanding patient and HCP experiences with telehealth and how telehealth compares to 'usual' care will be crucial in planning future CPC services. METHODOLOGY: All patients of the Barwon Health CPC service between 1 April and 31 May 2020 were invited to complete a questionnaire evaluating their interactions with the palliative care service and specifically their involvement with telehealth consultations. Palliative care HCP who provided clinical services during the same time period were also surveyed. RESULTS/CONCLUSION: Seventy-four patients (response rate 36%) and 22 HCP returned surveys. Both groups felt comfortable using telehealth, however, also encountered a range of issues when undertaking telehealth consultations. Despite reporting issues, the preference of both groups was for a CPC service model, which combined face-to-face and telehealth consultations. This study is one of the first to directly ask this question and as such provides useful guidance for health services when planning future CPC service models.

Evaluation of a Multidisciplinary Cachexia and Nutrition Support Service- The Patient and Carers Perspective.

The Barwon Health Cachexia & Nutrition Support Service (CNSS) is an outpatient service focused on improving clinical outcomes and quality of life for patients with or at high risk of cancer cachexia. Patients see a multidisciplinary team, comprising a palliative medicine physician, physiotherapist, dietitian, and nurse practitioner. This study evaluated the service from patient and carer perspectives. In 2016/17, semistructured interviews were conducted with 12 patients and 9 carers attending the service, focusing on: (1) reflection on experience of the CNSS, and (2) describing how a cachexia-specific service can meet their needs and concerns. Analysis generated 4 superordinate themes: evolving perception of service value, empowerment through person-centered care, communication to patients and carers regarding health/disease information, and the importance of the multidisciplinary team-based approach. Generally, patients and carers reported overall positive experiences with the service, particularly with regard to improved communication and management of the patient. Findings confirmed the patient-centered and individualized approaches were particularly valued. These insights are a critical step in the development of recommendations for future clinical management of cancer cachexia.

Managing Severe Chronic Breathlessness in Chronic Obstructive Pulmonary Disease Is Challenging for General Practitioners.

CONTEXT: Patients with advanced chronic obstructive pulmonary disease (COPD) can develop increasing breathlessness, which can persist despite optimal medical management-refractory breathlessness. Management can be challenging for all clinicians and requires a broad approach that includes optimization of disease directed therapies, non-pharmacological strategies to manage breathlessness and for some patients opioids. OBJECTIVES: To explore the approaches to breathlessness management and palliative care undertaken by Australian General Practitioners (GP) for patients with severe COPD and refractory breathlessness. METHODS: A case-vignette based survey was conducted with Australian GPs to determine their approaches to breathlessness management and palliative care in COPD. RESULTS: Of the 137 GPs, 66% recommended commencing an additional medication to manage refractory breathlessness. Thirty-eight GPs (28%) recommended opioids and 26 (19%) recommended guideline discordant treatments. Two-thirds of GPs had concerns regarding the use of opioids in COPD. Half (55%) of GPs were comfortable providing general palliative care to patients with COPD and 62 (45%) had referred patients with COPD to specialist palliative care services. Most respondents wanted further training to manage severe COPD and severe chronic breathlessness. CONCLUSION: Most GPs recognized and were willing to add specific treatments for severe chronic breathlessness. However, experience prescribing opioids for severe chronic breathlessness was low, with many practitioners holding significant concerns regarding adverse effects. Many GPs are uncomfortable offering a palliative approach to their COPD patients, yet these patients are not routinely referred to specialist palliative care services despite their immense needs. GPs therefore desire education and support to overcome these barriers.

Mapping non-malignant respiratory palliative care services in Australia and New Zealand.

Objective Despite needs, people with advanced non-malignant respiratory disease are infrequently referred to palliative care services. Integrated models of palliative care and respiratory service delivery have been advocated to address this inequity of access. This study mapped current ambulatory palliative care service provision for patients with advanced non-malignant respiratory disease in Australia and New Zealand. Methods An online survey was distributed to the palliative care physician membership of the Australian and New Zealand Society of Palliative Medicine. Information was sought regarding access to specific breathlessness and integrated respiratory and palliative care services, and their operation. Data were described using descriptive statistics. Results In all, 133 respondents (93 from Australia, 40 from New Zealand; representing 55 Australian and 26 New Zealand discrete sites) with complete data were available for analysis. More than half the respondents reported seeing patients with advanced non-malignant respiratory disease frequently (56/97; 58%), and 18 of 81 services (22%) reported having breathlessness or integrated respiratory and palliative care services caring for this patient group. Such services were mostly staffed by respiratory and palliative care doctors and nurses and based in the clinic environment, with limited support available outside this setting. Of the 63 respondents without existing breathlessness or integrated services, 49 (78%) expressed interest in their establishment, with limited resources cited as the most common barrier. Conclusions There is limited availability of integrated respiratory and palliative care or specialised breathlessness services in Australia and New Zealand despite widespread support by palliative care physicians. This study provides a snapshot to inform strategic service development. What is known about the topic? People with advanced respiratory disease have very significant morbidity with complex needs equivalent to, and in many cases more intense than, people with end-stage lung cancer; they also have significant mortality. Yet, these people frequently do not access palliative care services. The establishment of integrated respiratory and palliative care services has been advocated as an effective means to overcome the barriers to palliative care access. Such services have demonstrated improved patient and family-reported outcomes, as well as service-level improvements. What does this paper add? This paper maps the availability of integrated respiratory palliative care services in Australia and New Zealand. We reveal that although most palliative care physicians report seeing patients with advanced respiratory disease in practice, just one-fifth of services report having an integrated service approach. There was high interest and enthusiasm for such services (78%), but resources limited their establishment. What are the implications for practitioners? Palliative care services recognise the needs of patients with advanced respiratory disease and the benefits of integrated respiratory and palliative care services to address these needs, but scarcity of resources limits the ability to respond accordingly. This study provides a snapshot of current service level to inform strategic development.

Population-based analysis of radiotherapy and chemotherapy treatment in the last month of life within regional Australia.

BACKGROUND: Cancer treatment near end of life is not likely to add meaningful benefit and minimising intervention rates has been promoted as an indicator of quality of care. Population-based analysis of treatment allows comparative analysis of treatment rates and provides insight into patterns of care. AIMS: To report a population-based analysis of both radiotherapy and active systemic therapy (AST) delivery rates along with patterns of treatment within the last 14 and 30 days of life. METHODS: The Evaluation of Cancer Outcomes Registry records clinical information on all newly diagnosed cancer patients for the Barwon South West Region of Victoria, Australia. Diagnosis details, tumour type and stage as well as core treatment details and date of death were extracted for all patients diagnosed from 2009 to 2015 inclusive. RESULTS: A total of 12 760 cases cancers were recorded. The median age of all cases was 68.8, and 53% were male. AST was received by 3699 (29%) of patients and radiotherapy by 3811 (30%). Patient deaths within 14 and 30 days of treatment for AST were 4.3 and 8.7%, respectively, and deaths within 14 and 30 days of treatment for radiotherapy 3.8 and 8.0% respectively. Factors associated with death within 30 days of AST and/or radiotherapy were male gender, age greater than 70 years and higher disease stage (all P < 0.01). Treatment rates within 30 days of death were highest for lung cancer (23% of cases) and lowest for breast cancer (2% of cases). CONCLUSIONS: This population-based analysis of AST and radiotherapy treatment within the last 30 days of life within a region of Australia has shown overall treatment rates below 10%. Treatment rates appear influenced by both patient and tumour characteristics. Future focus on subgroups with high rates of late intervention may help minimise treatment unlikely to add benefit.

Use of clinical quality indicators to improve lung cancer care in a regional/rural network of health services.

PROBLEM: Optimal lung cancer care requires multidisciplinary team input, with access to specialised diagnostic and therapeutic services that may be limited in rural or regional areas and impact clinical outcomes. Clinical quality indicators can be used to measure the quality of care delivered to patients with lung cancer in a region and identify areas for improvement. We describe the implementation of internationally recognised clinical quality indicators for lung cancer care in the Barwon South Western region. DESIGN: The consensus of an expert panel was used for the selection of clinical quality indicators. The data were retrospectively collected from the Evaluation of Cancer Outcomes Barwon South West Registry, which systematically records detailed information on all new patients with cancer in the region. SETTING: Region-based health service. KEY MEASURES FOR IMPROVEMENT: Adherence to clinical quality indicator targets. STRATEGIES FOR CHANGE: Clinical quality indicators, which fall short of the expected targets, highlight areas for improvement in the service provided to patients with lung cancer. These results have prompted changes in the service offered to these patients, such as the introduction of a multidisciplinary lung cancer clinic. EFFECTS OF CHANGE: The multidisciplinary lung cancer clinic has streamlined the access to lung cancer services, including specialist consultations, diagnostics and therapeutic services, in a regional setting. Ongoing data collection is required to determine the effect of such changes on adherence to clinical quality indicator targets. LESSONS LEARNT: The regular monitoring of clinical quality indicators serves as a useful method of quality assurance in the care of patients with lung cancer. We expect these clinical quality indicators to also be used by other health services to analyse and improve services provided to patients with lung cancer.

The deteriorating patient representative on a palliative care quality committee: Ethical and practical considerations.

This case study describes the involvement of a patient representative on a palliative care committee and outlines some of the issues that arose as her health deteriorated. A summary of the increasing involvement of patient representation within health care governance is provided, and some of the challenges raised by the case, many of which may be relatively unique to palliative care, are discussed. It is hoped that presentation of this fairly novel scenario provides other palliative care providers with the opportunity to consider their own processes and practices around managing a similar situation should it occur in their healthcare setting.

Statistically Rigorous Silver Nanowire Diameter Distribution Quantification by Automated Electron Microscopy and Image Analysis.

Silver nanowire (AgNW) diameters are typically characterized by manual measurement from high magnification electron microscope images. Measurement is monotonous and has potential ergonomic hazards. Because of this, statistics regarding wire diameter distribution can be poor, costly, and low-throughput. In addition, manual measurements are of unknown uncertainty and operator bias. In this paper we report an improved microscopy method for diameter and yield measurement of nanowires in terms of speed/automation and reduction of analyst variability. Each step in the process to generate these measurements was analyzed and optimized: microscope imaging conditions, sample preparation for imaging, image acquisition, image analysis, and data processing. With the resulting method, average diameter differences between samples of just a few nanometers can be confidently and statistically distinguished, allowing the identification of subtle incremental improvements in reactor processing conditions, and insight into nucleation and growth kinetics of AgNWs.