Molecular subtypes in canine hemangiosarcoma reveal similarities with human angiosarcoma

Angiosarcoma (AS) is a rare neoplasm with limited treatment options and a poor survival rate. Development of effective therapies is hindered by the rarity of this disease. Dogs spontaneously develop hemangiosarcoma (HSA), a common, histologically similar neoplasm. Metastatic disease occurs rapidly and despite chemotherapy, most dogs die several months after diagnosis. These features suggest that HSA might provide a tractable model to test experimental therapies in clinical trials. We previously reported whole exome sequencing of 20 HSA cases. Here we report development of a NGS targeted resequencing panel to detect driver mutations in HSA and other canine tumors. We validated the panel by resequencing the original 20 cases and sequenced 30 additional cases. Overall, we identified potential driver mutations in over 90% of the cases, including well-documented (in human cancers) oncogenic mutations in PIK3CA (46%), PTEN (6%), PLCG1(4%), and TP53 (66%), as well as previously undetected recurrent activating mutations in NRAS (24%). The driver role of these mutations is further demonstrated by augmented downstream signaling crucial to tumor growth. The recurrent, mutually exclusive mutation patterns suggest distinct molecular subtypes of HSA. Driver mutations in some subtypes closely resemble those seen in some AS cases, including NRAS, PLCG1, PIK3CA and TP53. Furthermore, activation of the MAPK and PI3K pathways appear to be key oncogenic mechanisms in both species. Together, these observations suggest that dogs with spontaneous HSA could serve as a useful model for testing the efficacy of targeted therapies, some of which could potentially be of therapeutic value in AS.

Model-Informed Artificial Intelligence: Reinforcement Learning for Precision Dosing

The availability of multidimensional data together with the development of modern techniques for data analysis represent an exceptional opportunity for clinical pharmacology. Data science-defined in this special issue as the novel approaches to the collection, aggregation, and analysis of data-can significantly contribute to characterize drug-response variability at the individual level, thus enabling clinical pharmacology to become a critical contributor to personalized healthcare through precision dosing. We propose a minireview of methodologies for achieving precision dosing with a focus on an artificial intelligence technique called reinforcement learning, which is currently used for individualizing dosing regimen in patients with life-threatening diseases. We highlight the interplay of such techniques with conventional pharmacokinetic/pharmacodynamic approaches and discuss applicability in drug research and early development.

Effect of ursodeoxycholic acid therapy due to pregnant intrahepatic cholestasis on chemerin and irisin levels

The purpose of the work was to assess changes in chemerin and irisin levels in women with diagnosed intrahepatic cholestasis of pregnant women treated with ursodeoxycholic acid. The study group consisted of 50 patients with diagnosed and confirmed intrahepatic cholestasis of pregnant women at 24-25 weeks of pregnancy treatment by ursodeoxycholic acid (UDCA). The study also included a group of 40 pregnant women, without concomitant intrahepatic cholestasis of pregnancy (ICP). In the pregnant ICP group, whole blood was collected 4 times: before the first dose of drug, 4 and 8 weeks after the first dose, and day after delivery. It was observed that statistically significant differences in the concentration of irisine occur between the time before starting treatment and the 8-week therapy and 1 day after delivery. The Pearson correlation analysis (r's) showed two statistically significant relationships (p < .05). The first of these can be found between the concentration of irisine and chemerin in the group of nonpregnant women and the second in the group of patients with intrahepatic pregnant cholestasis before the first dose of UDCA. A significant relationship between irisin and chemerin concentrations was confirmed in the group of pregnant ICP patients during UDCA acid therapy and among healthy pregnant women.

Precision Medicine and Artificial Intelligence: A Pilot Study on Deep Learning for Hypoglycemic Events Detection based on ECG

Tracking the fluctuations in blood glucose levels is important for healthy subjects and crucial diabetic patients. Tight glucose monitoring reduces the risk of hypoglycemia, which can result in a series of complications, especially in diabetic patients, such as confusion, irritability, seizure and can even be fatal in specific conditions. Hypoglycemia affects the electrophysiology of the heart. However, due to strong inter-subject heterogeneity, previous studies based on a cohort of subjects failed to deploy electrocardiogram (ECG)-based hypoglycemic detection systems reliably. The current study used personalised medicine approach and Artificial Intelligence (AI) to automatically detect nocturnal hypoglycemia using a few heartbeats of raw ECG signal recorded with non-invasive, wearable devices, in healthy individuals, monitored 24 hours for 14 consecutive days. Additionally, we present a visualisation method enabling clinicians to visualise which part of the ECG signal (e.g., T-wave, ST-interval) is significantly associated with the hypoglycemic event in each subject, overcoming the intelligibility problem of deep-learning methods. These results advance the feasibility of a real-time, non-invasive hypoglycemia alarming system using short excerpts of ECG signal.

Recent advances in taste transduction and signaling

In the last few years, single-cell profiling of taste cells and ganglion cells has advanced our understanding of transduction, encoding, and transmission of information from taste buds as relayed to the central nervous system. This review focuses on new knowledge from these molecular approaches and attempts to place this in the context of previous questions and findings in the field. The individual taste cells within a taste bud are molecularly specialized for detection of one of the primary taste qualities: salt, sour, sweet, umami, and bitter. Transduction and transmitter release mechanisms differ substantially for taste cells transducing sour (Type  III cells) compared with those transducing the qualities of sweet, umami, or bitter (Type II cells), although ultimately all transmission of taste relies on activation of purinergic P2X receptors on the afferent nerves. The ganglion cells providing innervation to the taste buds also appear divisible into functional and molecular subtypes, and each ganglion cell is primarily but not exclusively responsive to one taste quality.

Engineering Requirements of a Herpes Simplex Virus Patient Registry: Discovery Phase of a Real-World Evidence Platform to Advance Pharmacogenomics and Personalized Medicine

Comprehensive pharmacogenomic understanding requires both robust genomic and demographic data. Patient registries present an opportunity to collect large amounts of robust, patient-level data. Pharmacogenomic advancement in the treatment of infectious diseases is yet to be fully realised. Herpes simplex virus (HSV) is one disease for which pharmacogenomic understanding is wanting. This paper aims to understand the key factors that impact data collection quality for medical registries and suggest potential design features of an HSV medical registry to overcome current constraints and allow for this data to be used as a complement to genomic and clinical data to further the treatment of HSV. This paper outlines the discovery phase for the development of an HSV registry with the aim of learning about the users and their contexts, the technological constraints and the potential improvements that can be made. The design requirements and user stories for the HSV registry have been identified for further alpha phase development. The current landscape of HSV research and patient registry development were discussed. Through the analysis of the current state of the art and thematic user analysis, potential design features were elucidated to facilitate the collection of high-quality, robust patient-level data which could contribute to advances in pharmacogenomic understanding and personalised medicine in HSV. The user requirements specification for the development of an HSV registry has been summarised and implementation strategies for the alpha phase discussed.

Precision dosing to avoid adverse drug reactions

Adverse drug reactions (ADRs) have traditionally been managed by trial and error, adjusting drug and dose selection reactively following patient harm. With an improved understanding of ADRs, and the patient characteristics that increase susceptibility, precision medicine technologies enable a proactive approach to ADRs and support clinicians to change prescribing accordingly. This commentary revisits the famous pharmacology–toxicology continuum first postulated by Paracelsus 500 years ago and explains why precision dosing is needed to help avoid ADRs in modern clinical practice. Strategies on how to improve precision dosing are given, including more research to establish better precision dosing targets in the cases of greatest need, easier access to dosing instructions via e-prescribing, improved monitoring of patients with novel biomarkers of drug response, and further application of model-informed precision dosing.

Dose-Response Matters! - A Perspective on the Exercise Prescription in Exercise-Cognition Research

In general, it is well recognized that both acute physical exercises and regular physical training influence brain plasticity and cognitive functions positively. However, growing evidence shows that the same physical exercises induce very heterogeneous outcomes across individuals. In an attempt to better understand this interindividual heterogeneity in response to acute and regular physical exercising, most research, so far, has focused on non-modifiable factors such as sex and different genotypes, while relatively little attention has been paid to exercise prescription as a modifiable factor. With an adapted exercise prescription, dosage can be made comparable across individuals, a procedure that is necessary to better understand the dose-response relationship in exercise-cognition research. This improved understanding of dose-response relationships could help to design more efficient physical training approaches against, for instance, cognitive decline.

Precision medicine technology hype or reality? The example of computer-guided dosing

Novel technologies labelled as ‘precision medicine’ are targeting all aspects of clinical care. Whilst some technological advances are undeniably exciting, many doctors at the frontline of healthcare view precision medicine as being out of reach for their patients. Computer-guided dosing is a precision medicine technology that predicts drug concentrations and drug responses based on individual patient characteristics. In this opinion piece, the example of computer-guided dosing is used to illustrate eight features of a precision medicine technology less likely to be hyperbole and more likely to improve patient care. Positive features in this regard include: (1) fitting the definition of ‘precision medicine’; (2) addressing a major clinical problem that negatively impacts patient care; (3) a track record of high-quality medical science published via peer-reviewed literature; (4) well-defined clinical cases for application; (5) quality evidence of benefits measured by various clinical, patient and health economic endpoints; (6) strong economic drivers; (7) user friendliness, including easy integration into clinical workflow, and (8) recognition of importance by patients and their endorsement for broader clinical use. Barriers raised by critics of the approach are given to balance the view. The value of computer-guided dosing will be decided ultimately by the extent to which it can improve cost-effective patient care.

Folate Receptor α-Targeted 89Zr-M9346A Immuno-PET for Image-Guided Intervention with Mirvetuximab Soravtansine in Triple-Negative Breast Cancer

Folate receptor α (FRα) is a well-studied tumor biomarker highly expressed in many epithelial tumors such as breast, ovarian, and lung cancers. Mirvetuximab soravtansine (IMGN853) is the antibody-drug conjugate of FRα-binding humanized monoclonal antibody M9346A and cytotoxic maytansinoid drug DM4. IMGN853 is currently being evaluated in multiple clinical trials, in which the immunohistochemical evaluation of an archival tumor or biopsy specimen is used for patient screening. However, limited tissue collection may lead to inaccurate diagnosis due to tumor heterogeneity. Herein, we developed a zirconium-89 (89Zr)-radiolabeled M9346A (89Zr-M9346A) as an immuno-positron emission tomography (immuno-PET) radiotracer to evaluate FRα expression in triple-negative breast cancer (TNBC) patients, providing a novel means to guide intervention with therapeutic IMGN853. In this study, we verified the binding specificity and immunoreactivity of 89Zr-M9346A by in vitro studies in FRαhigh cells (HeLa) and FRαlow cells (OVCAR-3). In vivo PET/computed tomography (PET/CT) imaging in HeLa xenografts and TNBC patient-derived xenograft (PDX) mouse models with various levels of FRα expression demonstrated its targeting specificity and sensitivity. Following PET imaging, the treatment efficiencies of IMGN853, pemetrexed, IMGN853 + pemetrexed, paclitaxel, and saline were assessed in FRαhigh and FRαlow TNBC PDX models. The correlation between 89Zr-M9346A tumor uptake and treatment response using IMGN853 in FRαhigh TNBC PDX model suggested the potential of 89Zr-M9346A PET as a noninvasive tool to prescreen patients based on the in vivo PET imaging for IMGN853-targeted treatment.

Oncoproteomics: Current status and future opportunities

Oncoproteomics is the systematic study of cancer samples using omics technologies to detect changes implicated in tumorigenesis. Recent progress in oncoproteomics is already opening new avenues for the identification of novel biomarkers for early clinical stage cancer detection, targeted molecular therapies, disease monitoring, and drug development. Such information will lead to new understandings of cancer biology and impact dramatically on the future care of cancer patients. In this review, we will summarize the advantages and limitations of the key technologies used in (onco)proteogenomics, (the Omics Pipeline), explain how they can assist us in understanding the biology behind the overarching "Hallmarks of Cancer", discuss how they can advance the development of precision/personalised medicine and the future directions in the field.

Spatial, Temporal, and Dose Control of Drug Delivery using Noninvasive Magnetic Stimulation

Noninvasive stimuli-responsive drug delivery using magnetic fields in conjunction with superparamagnetic nanoparticles offers the potential for the spatial and temporal control of drug release. When hyperthermia is not desired and control of the dosage is required, it is necessary to design a platform in which local heating on the nanoscale releases the therapeutic cargo without the bulk heating of the surrounding medium. In this paper, we report a design using a stimuli-responsive nanoparticle platform to control the dosage of the cargo released by an alternating magnetic field (AMF) actuation. A core@shell structure with a superparamagnetic doped iron oxide (MnFe₂O₄@CoFe₂O₄) nanoparticle core in a mesoporous silica shell was synthesized. The core used here has a high saturation magnetization value and a high specific loss power for heat generation under an AMF. The mesoporous shell has a high cargo-carrying capacity. A thermoresponsive molecular-based gatekeeper containing an aliphatic azo group was modified on the core@shell nanoparticles to regulate the cargo release. The mesoporous structure of the silica shell remained intact after exposure to an AMF, showing that the release of cargo is due to the removal of the gatekeepers instead of the destruction of the structure. Most importantly, we demonstrated that the amount of cargo released could be adjusted by the AMF exposure time. By applying multiple sequential exposures of AMF, we were able to release the cargo step-wise and increase the total amount of released cargo. In vitro studies showed that the death of pancreatic cancer cells treated by drug-loaded nanoparticles was controlled by different lengths of AMF exposure time due to different amount of drugs released from the carriers. The strategy developed here holds great promise for achieving the dosage, temporal, and spatial control of therapeutics delivery without the risk of overheating the particles' surroundings.

Optimal adaptive control of drug dosing using integral reinforcement learning

In this paper, a reinforcement learning (RL)-based optimal adaptive control approach is proposed for the continuous infusion of a sedative drug to maintain a required level of sedation. To illustrate the proposed method, we use the common anesthetic drug propofol used in intensive care units (ICUs). The proposed online integral reinforcement learning (IRL) algorithm is designed to provide optimal drug dosing for a given performance measure that iteratively updates the control solution with respect to the pharmacology of the patient while guaranteeing convergence to the optimal solution. Numerical results are presented using 10 simulated patients that demonstrate the efficacy of the proposed IRL-based controller.

What Does it Take to Make Model-Informed Precision Dosing Common Practice? Report from the 1st Asian Symposium on Precision Dosing

Model-informed precision dosing (MIPD) is modeling and simulation in healthcare to predict the drug dose for a given patient based on their individual characteristics that is most likely to improve efficacy and/or lower toxicity in comparison to traditional dosing. This paper describes the background and status of MIPD and the activities at the 1st Asian Symposium of Precision Dosing. The theme of the meeting was the question, "What does it take to make MIPD common practice?" Formal presentations highlighted the distinction between genetic and non-genetic sources of variability in drug exposure and response, the use of modeling and simulation as decision support tools, and the facilitators to MIPD implementation. A panel discussion addressed the types of models used for MIPD, how the pharmaceutical industry views MIPD, ways to upscale MIPD beyond academic hospital centers, and the essential role of healthcare professional education as a way to progress. The meeting concluded with an ongoing commitment to use MIPD to improve patient care.

Natural selection and local adaptation of blood pressure regulation and their perspectives on precision medicine in hypertension

Prevalence of hypertension (HTN) varies substantially across different populations. HTN is not only common - affecting at least one third of the world's adult population - but is also the most important driver for cardiovascular diseases. Yet up to a third of hypertensive patients are resistant to therapy, contributed by secondary hypertension but more commonly the hitherto inability to precisely predict response to specific antihypertensive agents. Population and individual genomics information could be useful in guiding the selection and predicting the response to treatment - an approach known as precision medicine. However this cannot be achieved without the knowledge of genetic variations that influence blood pressure (BP). A number of evolutionary factors including population demographics and forces of natural selection may be involved. This article explores some ideas on how natural selection influences BP regulation in ethnically and geographically diverse populations that could lead to them being susceptible to HTN. We explore how such evolutionary factors could impact the implementation of precision medicine in HTN. Finally, in order to ensure the success of precision medicine in HTN, we call for more initiatives to understand the genetic architecture within and between diverse populations with ancestry from different parts of the world, and to precisely classify the intermediate phenotypes of HTN.

New frontiers in precision medicine for sepsis-induced immunoparalysis

INTRODUCTION

In the last decade, the sepsis research field has shifted focus from targeting hyperinflammation to reversing sepsis-induced immunoparalysis. Sepsis-induced immunoparalysis is very heterogeneous: the magnitude and the nature of the underlying immune defects differ considerably between patients, but also within individuals over time. Therefore, a 'one-treatment-fits-all' strategy for sepsis-induced immunoparalysis is bound to fail, and an individualized 'precision medicine' approach is required. Such a strategy is nevertheless hampered by the unsuitability of the currently available markers to identify the many immune defects that can manifest in individual patients. Areas covered: We describe the currently available markers for sepsis-induced immunoparalysis and limitations pertaining to their use. Furthermore, future prospects and caveats are discussed, focusing on 'omics' approaches: genomics, transcriptomics, epigenomics, and metabolomics. Finally, we present a contemporary overview of adjuvant immunostimulatory therapies. Expert opinion: The integration of multiple omics techniques offers a systems biology approach which can yield biomarker profiles that accurately and comprehensively gauge the extent and nature of sepsis-induced immunoparalysis. We expect this development to be instrumental in facilitating precision medicine for sepsis-induced immunoparalysis, consisting of the application of targeted immunostimulatory therapies and follow-up measurements to monitor the response to treatment and to titrate or adjust medication.

Introduction to the Theme “New Therapeutic Targets”

“New Therapeutic Targets” is the theme of articles in the Annual Review of Pharmacology and Toxicology, Volume 59. Reviews in this volume discuss targets for a variety of conditions in need of new therapies, including type 2 diabetes, heart failure with preserved ejection fraction, obesity, thyroid-associated ophthalmopathy, tinnitus, multiple sclerosis, Parkinson's disease and other neurodegenerative diseases, pain, depression, post-traumatic stress disorder, muscle wasting diseases, cancer, and anemia associated with chronic renal disease. Numerous articles in this volume focus on the identification, validation, and utility of novel therapeutic targets, in particular, ones that involve new or unexpected molecular entities. This theme complements several previous themes, including “New Approaches for Studying Drug and Toxicant Action: Applications to Drug Discovery and Development,” “Precision Medicine and Prediction in Pharmacology,” and “New Methods and Novel Therapeutic Approaches in Pharmacology and Toxicology.”

Estimating Renal Function in Drug Development: Time to Take the Fork in the Road

Renal function is the most commonly applied patient-specific quantitative variable used to determine drug doses. Measurement of renal function is not practical in most clinical settings; therefore, clinicians often rely on estimates when making dosing decisions. Similarly, renal function estimates are used to assign subjects in phase 1 pharmacokinetic studies, which inform dosing in late-phase clinical trials and ultimately the product label. The Cockcroft-Gault estimate of creatinine clearance has been the standard renal function metric; however, this paradigm is shifting toward the Modification of Diet in Renal Diseases (MDRD) estimate of the glomerular filtration rate (GFR). The proportion of approved new drug labels with dosing recommendations based on the MDRD equation was 16.7% in 2015, 70.0% in 2016, and 46.7% in 2017. Disharmonious recommendations from the United States Food and Drug Administration and the European Medicines Agency will continue to increase this heterogeneity in the assessment of renal function in drug development and negatively impact industry, health systems, and clinicians. In this review, we discuss the current regulatory guidance for the conduct of renal impairment pharmacokinetic studies and review the implications of this guidance across the medication use system with 3 recently approved antibiotics: ceftazidime/avibactam, delafloxacin, and meropenem/vaborbactam. Finally, we suggest measuring GFR in phase 1 studies and employing the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation to integrate data across clinical trials. This will help to harmonize CKD staging, population pharmacokinetic analyses, and dosing by estimated renal function.

Advancing precision medicine with personalized drug screening

Personalized drug screening (PDS) of approved drug libraries enables rapid development of specific small-molecule therapies for individual patients. With a multidisciplinary team including clinicians, researchers, ethicists, informaticians and regulatory professionals, patient treatment can be optimized with greater efficacy and fewer adverse effects by using PDS as an approach to find remedies. In addition, PDS has the potential to rapidly identify therapeutics for a patient suffering from a disease without an existing therapy. From cancer to bacterial infections, we review specific maladies addressed with PDS campaigns. We predict that PDS combined with personal genomic analyses will contribute to the development of future precision medicine endeavors.

Mesoporous silica nanoparticles facilitating the dissolution of poorly soluble drugs in orodispersible films

Orodispersible films (ODF) are immediately dissolving/disintegrating intraoral dosage forms, presented as substitutes of conventional tablets or capsules to ease problems associated with swallowing. Efforts have been made to be able to exploit ODFs as dosage forms for poorly soluble drugs. In the last two decades, mesoporous silica nanoparticles (MSNs) have been extensively used in drug delivery applications to overcome solubility problems of drugs. The tunable features of MSNs make them suitable candidates as drug carriers and solubility enhancers. In this study, the feasibility of MSNs as a carrier of poorly soluble drugs, using prednisolone as a model drug, in ODFs was investigated. Our results revealed that the increased amount of MSNs in ODFs leads to shortening of the disintegration time of the films. Drug content investigations showed that low dose ODFs with prednisolone incorporation efficiencies higher than 80% could be produced. Furthermore, the prednisolone release profile from ODFs can be tuned with the incorporation of MSNs as drug carrier (MSN_pred). The MSN_pred incorporated ODFs yield with immediate release of drug from the ODF, whereby 90% of the prednisolone content could be released in the first minutes. By modifying the MSN_pred design with copolymer surface coating, prednisolone (cop-MSN_pred) release can be modulated into a two-step sustained release profile. To sum up, the MSNs platform does not only provide careful low dose incorporation into ODF with high efficiency, but it also aids in tuning the drug release profiles from ODFs.

Introduction to the Theme "New Approaches for Studying Drug and Toxicant Action: Applications to Drug Discovery and Development"

The theme "New Approaches for Studying Drug and Toxicant Action: Applications to Drug Discovery and Development" links 13 articles in this volume of the Annual Review of Pharmacology and Toxicology (ARPT). The engaging prefatory articles by Arthur Cho and Robert Lefkowitz set the stage for this theme and for the reviews that insightfully describe new approaches that advance research and discovery in pharmacology and toxicology. Examples include the progress being made in developing Organs-on-Chips/microphysiological systems and human induced pluripotent stem cell-derived cells to aid in understanding cell and tissue pharmacokinetics, action, and toxicity; the recognition of the importance of circadian rhythm, the microbiome, and epigenetics in drug and toxicant responses; and the application of results from new types of patient-derived information to create personalized/precision medicine, including therapeutics for pain, which may perhaps provide help in dealing with the opioid epidemic in the United States. Such new information energizes discovery efforts in pharmacology and toxicology that seek to improve the efficacy and safety of drugs in patients and to minimize the consequences of exposure to toxins.