preon: Fast and accurate entity normalization for drug names and cancer types in precision oncology

MOTIVATION

In precision oncology (PO), clinicians aim to find the best treatment for any patient based on their molecular characterization. A major bottleneck is the manual annotation and evaluation of individual variants, for which usually a range of knowledge bases are screened. To incorporate and integrate the vast information of different databases, fast and accurate methods for harmonizing databases with different types of information are necessary. An essential step for harmonization in PO includes the normalization of tumor entities as well as therapy options for patients.

SUMMARY

preon is a fast and accurate library for the normalization of drug names and cancer types in large-scale data integration.

AVAILABILITY AND IMPLEMENTATION

preon is implemented in Python and freely available via the PyPI repository. Source code and the data underlying this article are available in GitHub at https://github.com/ermshaua/preon/.

New windows of surgical opportunity for gynecological cancers in the era of targeted therapies

Precision medicine through molecular profiling has taken a prominent role in the treatment of solid tumors and it is widely expected that this will continue to expand. With respect to gynecological cancers, a major change has particularly been observed in the treatment landscape of epithelial ovarian, endometrial, and cervical cancers. Regarding the former, maintenance therapy with either poly(ADP-ribose) polymerase inhibitors (PARPi) and/or bevacizumab has become an indispensable treatment option following the traditional combination of cytoreductive surgery and platinum-based chemotherapy. Considering endometrial cancer, the molecular classification system has now been incorporated into virtually every guideline available and molecular-directed treatment strategies are currently being researched, presumably leading to a further transformation of its treatment paradigm. After all, treatment with immune-checkpoint inhibitors that target the programmed cell death 1 (PD-1) receptor has already been shown to significantly improve disease outcomes in these patients, especially in those with mismatch repair deficient, microsatellite stability-high (MMRd-MSI-H) disease. Similarly, in recurrent/metastatic cervical cancer patients, these agents elicited improved survival rates when being added to platinum-based chemotherapy with or without bevacizumab. Interestingly, implications of these targeted therapies for surgical management have been touched on to a minor extent, but are at least as intriguing. This review therefore aims to address the wide-ranging opportunities the molecular tumor characteristics and their corresponding targeted therapies have to offer for the surgical management of epithelial ovarian, endometrial, and cervical cancers, both in the primary and recurrent setting.

Advances in targeted therapy and biomarker research in thyroid cancer

Driven by the intricacy of the illness and the need for individualized treatments, targeted therapy and biomarker research in thyroid cancer represent an important frontier in oncology. The variety of genetic changes associated with thyroid cancer demand more investigation to elucidate molecular details. This research is clinically significant since it can be used to develop customized treatment plans. A more focused approach is provided by targeted therapies, which target certain molecular targets such as mutant BRAF or RET proteins. This strategy minimizes collateral harm to healthy tissues and may also reduce adverse effects. Simultaneously, patient categorization based on molecular profiles is made possible by biomarker exploration, which allows for customized therapy regimens and maximizes therapeutic results. The benefits of targeted therapy and biomarker research go beyond their immediate clinical impact to encompass the whole cancer landscape. Comprehending the genetic underpinnings of thyroid cancer facilitates the creation of novel treatments that specifically target aberrant molecules. This advances the treatment of thyroid cancer and advances precision medicine, paving the way for the treatment of other cancers. Taken simply, more study on thyroid cancer is promising for better patient care. The concepts discovered during this investigation have the potential to completely transform the way that care is provided, bringing in a new era of personalized, precision medicine. This paradigm shift could improve the prognosis and quality of life for individuals with thyroid cancer and act as an inspiration for advances in other cancer types.

New clinical trial design in precision medicine: discovery, development and direction

In the era of precision medicine, it has been increasingly recognized that individuals with a certain disease are complex and different from each other. Due to the underestimation of the significant heterogeneity across participants in traditional "one-size-fits-all" trials, patient-centered trials that could provide optimal therapy customization to individuals with specific biomarkers were developed including the basket, umbrella, and platform trial designs under the master protocol framework. In recent years, the successive FDA approval of indications based on biomarker-guided master protocol designs has demonstrated that these new clinical trials are ushering in tremendous opportunities. Despite the rapid increase in the number of basket, umbrella, and platform trials, the current clinical and research understanding of these new trial designs, as compared with traditional trial designs, remains limited. The majority of the research focuses on methodologies, and there is a lack of in-depth insight concerning the underlying biological logic of these new clinical trial designs. Therefore, we provide this comprehensive review of the discovery and development of basket, umbrella, and platform trials and their underlying logic from the perspective of precision medicine. Meanwhile, we discuss future directions on the potential development of these new clinical design in view of the "Precision Pro", "Dynamic Precision", and "Intelligent Precision". This review would assist trial-related researchers to enhance the innovation and feasibility of clinical trial designs by expounding the underlying logic, which be essential to accelerate the progression of precision medicine.

The Effects of Animations and Multimedia Messages on Public Engagement in Precision Medicine: Assessment of Moderation and Mediation

Public participation in precision medicine (PM) research is essential to achieving effective health care but has been impeded by a lack of awareness and basic knowledge. There is a critical need for educational materials that can clearly explain PM to foster involvement. This randomized controlled trial with a posttest-only control group design aims to assess the effects of educational messages delivered through animations relative to live-action videos and leaflets on intentions of involvement in PM research. Knowledge as the moderator and four mediators (engagement, vividness, trustworthiness, and cognitive value) of the intended effects were also evaluated. A total of 326 U.S. adults were sampled from Amazon Mechanical Turk. Among participants with less knowledge about PM, animations produced stronger information-seeking intentions and willingness to participate than leaflets. The effects of three message modalities were not significantly different among average and highly knowledgeable participants. Engagement and vividness mediated the effects of animations relative to two other message modalities. Trustworthiness and cognitive value mediated the effects of animations relative to live-action videos. Overall, animations can be an effective communication strategy to motivate involvement in PM but its effectiveness could decline as knowledge increases. The explanations and implications of the findings were discussed.

Therapeutic potential of mitochondrial transplantation in modulating immune responses post-cardiac arrest: a narrative review

BACKGROUND

Mitochondrial transplantation (MTx) has emerged as a novel therapeutic strategy, particularly effective in diseases characterized by mitochondrial dysfunction. This review synthesizes current knowledge on MTx, focusing on its role in modulating immune responses and explores its potential in treating post-cardiac arrest syndrome (PCAS).

METHODS

We conducted a comprehensive narrative review of animal and human studies that have investigated the effects of MTx in the context of immunomodulation. This included a review of the immune responses following critical condition such as ischemia reperfusion injury, the impact of MTx on these responses, and the therapeutic potential of MTx in various conditions.

RESULTS

Recent studies indicate that MTx can modulate complex immune responses and reduce ischemia-reperfusion injury post-CA, suggesting MTx as a novel, potentially more effective approach. The review highlights the role of MTx in immune modulation, its potential synergistic effects with existing treatments such as therapeutic hypothermia, and the need for further research to optimize its application in PCAS. The safety and efficacy of autologous versus allogeneic MTx, particularly in the context of immune reactions, are critical areas for future investigation.

CONCLUSION

MTx represents a promising frontier in the treatment of PCAS, offering a novel approach to modulate immune responses and restore cellular energetics. Future research should focus on long-term effects, combination therapies, and personalized medicine approaches to fully harness the potential of MTx in improving patient outcomes in PCAS.

Patterns and determinants of response to novel therapies in juvenile and adult-onset polyarthritis

Biologic and targeted synthetic DMARDs (b/tsDMARDs) have revolutionized the management of multiple rheumatic inflammatory conditions. Among these, polyarticular JIA (pJIA) and RA display similarities in terms of disease pathophysiology and response pattern to b/tsDMARDs. Indeed, the therapeutic efficacy of novel targeted drugs is variable among individual patients, in both RA and pJIA. The mechanisms and determinants of this heterogeneous response are diverse and complex, such that the development of true 'precision'-medicine strategies has proven highly challenging. In this review, we will discuss pathophysiological, patient-specific, drug-specific and environmental factors contributing to individual therapeutic response in pJIA in comparison with what is known in RA. Although some biomarkers have been identified that stratify with respect to the likelihood of either therapeutic response or non-response, few have proved useful in clinical practice so far, likely due to the complexity of treatment-response mechanisms. Consequently, we propose a pragmatic, patient-centred and clinically based approach, i.e. personalized instead of biomarker-based precision medicine in JIA.

Cholangiocarcinoma: Pathologic and Molecular Classification in the Era of Precision Medicine

CONTEXT.—

Cholangiocarcinoma (CCA) is a heterogeneous cancer of the bile duct, and its diagnosis is often challenging.

OBJECTIVE.—

To provide insights into state-of-the-art approaches for the diagnosis of CCA.

DATA SOURCES.—

Literature review via PubMed search and authors' experiences.

CONCLUSIONS.—

CCA can be categorized as intrahepatic or extrahepatic. Intrahepatic CCA is further classified into small-duct-type and large-duct-type, whereas extrahepatic CCA is classified into distal and perihilar according to site of origin within the extrahepatic biliary tree. Tumor growth patterns include mass forming, periductal infiltrating, and intraductal tumors. The clinical diagnosis of CCA is challenging and usually occurs at an advanced tumor stage. Pathologic diagnosis is made difficult by tumor inaccessibility and challenges in distinguishing CCA from metastatic adenocarcinoma to the liver. Immunohistochemical stains can assist in differentiating CCA from other malignancies, such as hepatocellular carcinoma, but no distinctive CCA-specific immunohistochemical profile has been identified. Recent advances in next-generation sequencing-based high-throughput assays have identified distinct genomic profiles of CCA subtypes, including genomic alterations that are susceptible to targeted therapies or immune checkpoint inhibitors. Detailed histopathologic and molecular evaluations of CCA by pathologists are critical for correct diagnosis, subclassification, therapeutic decision-making, and prognostication. The first step toward achieving these goals is to acquire a detailed understanding of the histologic and genetic subtypes of this heterogeneous tumor group. Here, we review state-of-the-art approaches that should be applied to establish a diagnosis of CCA, including clinical presentation, histopathology, staging, and the practical use of genetic testing methodologies.

Personalized Drug Therapy: Innovative Concept Guided With Proteoformics

Personalized medicine can reduce adverse effects, enhance drug efficacy, and optimize treatment outcomes, which represents the essence of personalized medicine in the pharmacy field. Protein drugs are crucial in the field of personalized drug therapy and are currently the mainstay, which possess higher target specificity and biological activity than small-molecule chemical drugs, making them efficient in regulating disease-related biological processes, and have significant potential in the development of personalized drugs. Currently, protein drugs are designed and developed for specific protein targets based on patient-specific protein data. However, due to the rapid development of two-dimensional gel electrophoresis and mass spectrometry, it is now widely recognized that a canonical protein actually includes multiple proteoforms, and the differences between these proteoforms will result in varying responses to drugs. The variation in the effects of different proteoforms can be significant and the impact can even alter the intended benefit of a drug, potentially making it harmful instead of lifesaving. As a result, we propose that protein drugs should shift from being targeted through the lens of protein (proteomics) to being targeted through the lens of proteoform (proteoformics). This will enable the development of personalized protein drugs that are better equipped to meet patients' specific needs and disease characteristics. With further development in the field of proteoformics, individualized drug therapy, especially personalized protein drugs aimed at proteoforms as a drug target, will improve the understanding of disease mechanisms, discovery of new drug targets and signaling pathways, provide a theoretical basis for the development of new drugs, aid doctors in conducting health risk assessments and making more cost-effective targeted prevention strategies conducted by artificial intelligence/machine learning, promote technological innovation, and provide more convenient treatment tailored to individualized patient profile, which will benefit the affected individuals and society at large.

Liquid biopsy: New opportunities for precision medicine in hepatocellular carcinoma care

Liquid biopsy, specifically the analysis of circulating tumor DNA (ctDNA), offers a non-invasive approach for hepatocellular carcinoma (HCC) diagnosis and management. However, its implementation in the clinical setting is difficult due to challenges such as low ctDNA yield and difficulty in understanding the mutation signals from background noise. This review highlights the crucial role of artificial intelligence (AI) in addressing these limitations and in improving discoveries in the field of liquid biopsy for HCC care. Combining AI with liquid biopsy data can offer a promising future for the discovery of novel biomarkers and an AI-powered clinical decision support system (CDSS) can turn liquid biopsy into an important tool for personalized management of HCC. Despite the current challenges, the integration of AI shows promise to significantly improve patient outcomes and revolutionize the field of oncology.

Nanocatalytic theranostics with intracellular mutual promotion for ferroptosis and chemo-photothermal therapy

The reactive oxygen species (ROS) produced through the Fenton reaction, induces lipid peroxide (LPO), causing cellular structural damage and ultimately triggering ferroptosis. However, the generation of ROS in the tumor microenvironment (TME) is limited by the catalytic efficiency of the Fenton reaction. Herein, a novel hollow mesoporous silica nanoparticle (HMSN) combined with multi-metal sulfide-doped mesoporous silica nanocatalyzers (NCs) was developed, namely MxSy-HMSN NCs (M represents Cu Mn and Fe, S denotes sulfur). The MxSy-HMSN can dramatically enhanced the ferroptosis by: (1) facilitating the conversion of H2O2 to ·OH through Fenton or Fenton-like reactions through co-catalysis; (2) weakening ROS scavenging systems by depleting the over expressed glutathione (GSH) in TME; (3) providing exceptional photothermal therapy to augment ferroptosis. The MxSy-HMSN can also act as smart cargos for anticancer drug-doxorubicin (DOX). The release of DOX is responsive to GSH/pH/Near-infrared Light (NIR) irradiation at the tumor lesion, significantly improving therapeutic outcomes while minimizing side effects. Additionally, the MxSy-HMSN has demonstrated excellent magnetic resonance imaging (MRI) potential. This smart MxSy-HMSN offer a synergetic approach combining ferroptosis with chemo-photothermal therapy and magnetic resonance imaging (MRI) diagnose, which could be an informative guideline for the design of future NCs.

Advances in artificial intelligence for the diagnosis and treatment of ovarian cancer (Review)

Artificial intelligence (AI) has emerged as a crucial technique for extracting high‑throughput information from various sources, including medical images, pathological images, and genomics, transcriptomics, proteomics and metabolomics data. AI has been widely used in the field of diagnosis, for the differentiation of benign and malignant ovarian cancer (OC), and for prognostic assessment, with favorable results. Notably, AI‑based radiomics has proven to be a non‑invasive, convenient and economical approach, making it an essential asset in a gynecological setting. The present study reviews the application of AI in the diagnosis, differentiation and prognostic assessment of OC. It is suggested that AI‑based multi‑omics studies have the potential to improve the diagnostic and prognostic predictive ability in patients with OC, thereby facilitating the realization of precision medicine.

Systematic Review Article: New Drug Strategies for Treating Resistant Hypertension-the Importance of a Mechanistic, Personalized Approach

Resistant hypertension (RHT) is characterized by persistently high blood pressure (BP) levels above the widely recommended therapeutic targets of less than 140/90 mmHg office BP, despite life-style measures and optimal medical therapies, including at least three antihypertensive drug classes at maximum tolerated dose (one should be a diuretic). This condition is strongly related to hypertension-mediated organ damage and, mostly, high risk of hospitalization due to hypertension emergencies or acute cardiovascular events. Hypertension guidelines proposed a triple combination therapy based on renin angiotensin system blocking agent, a thiazide or thiazide-like diuretic, and a dihydropyridinic calcium-channel blocker, to almost all patients with RHT, who should also receive either a beta-blocker or a mineralocorticoid receptor antagonist, or both, depending on concomitant conditions and contraindications. Several other drugs may be attempted, when elevated BP levels persist in these RHT patients, although their added efficacy in lowering BP levels on top of optimal medical therapy is uncertain. Also, renal denervation has demonstrated to be a valid therapeutic alternative in RHT patients. More recently, novel drug classes and molecules have been tested in phase 2 randomised controlled clinical trials in patients with RHT on top of optimal medical therapy with at least 2-3 antihypertensive drugs. These novel drugs, which are orally administered and are able to antagonize different pathophysiological pathways, are represented by non-steroid mineralocorticorticoid receptor antagonists, selective aldosterone synthase inhibitors, and dual endothelin receptor antagonists, all of which have proven to reduce seated office and 24-h ambulatory systolic/diastolic BP levels. The main findings of randomized clinical trials performed with these drugs  as well as their potential indications for the clinical management of RHT patients are summarised in this systematic review article.

A carbonic anhydrase-targeted NIR-II fluorescent cisplatin theranostic nanoparticle for combined therapy of pancreatic tumors

Optically active organic nanoparticles capable of emitting strong near-infrared II (NIR-II) fluorescence and eliciting tumor hyperthermia are promising for tumor imaging and photothermal therapy (PTT). However, their applications for the treatment of pancreatic tumors via mere PTT are challenging as both the nanoparticles and light are hard to enter the deeply located pancreatic tumors. Here, we report a NIR-II light excitable, carbonic anhydrase (CA)-targeting cisplatin prodrug-decorated nanoparticle (IRNPs-SBA/PtIV) for NIR-II fluorescence imaging (FLI)-guided combination PTT and chemotherapy of pancreatic tumors. IRNPs-SBA/PtIV is designed to hold a high photothermal conversion efficiency (PCE ≈ 65.17 %) under 1064 nm laser excitation, a strong affinity toward CA (Kd = 14.40 ± 5.49 nM), and a prominent cisplatin release profile in response to glutathione (GSH) and 1064 nm laser irradiation. We show that IRNPs-SBA/PtIV can be actively delivered into pancreatic tumors where the CA is upregulated, and emits NIR-II fluorescence to visualize tumors with a high sensitivity and penetration depth under 980 nm laser excitation. Moreover, the tumor-resided IRNPs-SBA/PtIV can efficiently inhibit the CA activity and consequently, relieve the acidic and hypoxic tumor microenvironment, benefiting to intensify chemotherapy. Guided by the NIR-II FLI, IRNPs-SBA/PtIV is capable of efficiently inhibiting pancreatic tumor growth via combinational PTT and chemotherapy with 1064 nm laser excitation under a low-power density (0.5 W cm-2, 10 min). This study demonstrates promise to fabricate NIR-II excitable nanoparticles for FLI-guided precise theranostics of pancreatic tumors.

Explore & actuate: the future of personalized medicine in oncology through emerging technologies

PURPOSE OF REVIEW

The future of medicine is aimed to equip the physician with tools to assess the individual health of the patient for the uniqueness of the disease that separates it from the rest. The integration of omics technologies into clinical practice, reviewed here, would open new avenues for addressing the spatial and temporal heterogeneity of cancer. The rising cancer burden patiently awaits the advent of such an approach to personalized medicine for routine clinical settings.

RECENT FINDINGS

To weigh the translational potential, multiple technologies were categorized based on the extractable information from the different types of samples used, to the various omic-levels of molecular information that each technology has been able to advance over the last 2 years. This review uses a multifaceted classification that helps to assess translational potential in a meaningful way toward clinical adaptation.

SUMMARY

The importance of distinguishing technologies based on the flow of information from exploration to actuation puts forth a framework that allows the clinicians to better adapt a chosen technology or use them in combination to enhance their goals toward personalized medicine.

Theranostic DNA nanostructure based on phenotype-specific activation of antisense oligonucleotides

Antisense oligonucleotide (ASO) is a powerful agent for gene therapy, designed to form complementary pairs with specific mRNA to inhibit gene expression. However, low specificity limits its potential. To overcome this challenge, we developed a Y-shape DNA nanostructure that enhances the specificity in ASO-based treatment by introducing a detection trigger. The design incorporates the phenotype-specific miR21 activation and the sequential release of Bcl2 ASO. As a result, our Y-shape DNA nanostructure downregulates >50 % Bcl2 mRNA expression and induces >60 % cell death in breast cancer cells. Meanwhile, this approach shows no obvious damage to the non-cancerous cells, indicating the therapeutic potential as a theranostics agent in precision medicine with the combination of biomarker sensing and treatment. Overall, our Y-shape DNA nanostructure serves as a promising strategy providing potential in customized conformation design with specific target sequences in gene therapy.

New precision medicine avenues to the prevention of Alzheimer's disease from insights into the structure and function of γ-secretases

Two phase-III clinical trials with anti-amyloid peptide antibodies have met their primary goal, i.e. slowing of Alzheimer's disease (AD) progression. However, antibody therapy may not be the optimal therapeutic modality for AD prevention, as we will discuss in the context of the earlier small molecules described as "γ-secretase modulators" (GSM). We review here the structure, function, and pathobiology of γ-secretases, with a focus on how mutations in presenilin genes result in early-onset AD. Significant progress has been made in generating compounds that act in a manner opposite to pathogenic presenilin mutations: they stabilize the proteinase-substrate complex, thereby increasing the processivity of substrate cleavage and altering the size spectrum of Aβ peptides produced. We propose the term "γ-secretase allosteric stabilizers" (GSAS) to distinguish these compounds from the rather heterogenous class of GSM. The GSAS represent, in theory, a precision medicine approach to the prevention of amyloid deposition, as they specifically target a discrete aspect in a complex cell biological signalling mechanism that initiates the pathological processes leading to Alzheimer's disease.

NIMEQ-SACNet: A novel self-attention precision medicine model for vision-threatening diabetic retinopathy using image data

In the realm of precision medicine, the potential of deep learning is progressively harnessed to facilitate intricate clinical decision-making, especially when navigating multifaceted datasets encompassing Omics, Clinical, image, device, social, and environmental dimensions. This study accentuates the criticality of image data, given its instrumental role in detecting and classifying vision-threatening diabetic retinopathy (VTDR) - a predominant global contributor to vision impairment. The timely identification of VTDR is a linchpin for efficacious interventions and the mitigation of vision loss. Addressing this, This study introduces "NIMEQ-SACNet," a novel hybrid model by the prowess of the Enhanced Quantum-Inspired Binary Grey Wolf Optimizer (EQI-BGWO) with a self-attention capsule network. The proposed approach is characterized by two pivotal advancements: firstly, the augmentation of the Binary Grey Wolf Optimization through Quantum Computing methodologies, and secondly, the deployment of the enhanced EQI-BGWO to adeptly calibrate the SACNet's parameters, culminating in a notable uplift in VTDR classification accuracy. The proposed model's ability to handle binary, 5-stage, and 7-stage VTDR classifications adroitly is noteworthy. Rigorous assessments on the fundus image dataset, underscored by metrics such as Accuracy, Sensitivity, Specificity, Precision, F1-Score, and MCC, bear testament to NIMEQ-SACNet's pre-eminence over prevailing algorithms and classification frameworks.

Using anti-PD-L1 antibody conjugated gold nanoshelled poly (Lactic-co-glycolic acid) nanocapsules loaded with doxorubicin: A theranostic agent for ultrasound imaging and photothermal/chemo combination therapy of triple negative breast cancer

Triple negative breast cancer (TNBC) has the worst prognosis of all breast cancers, and it is difficult to progress through traditional chemotherapy. Therefore, the treatment of TNBC urgently requires agents with effective diagnostic and therapeutic capabilities. In this study, we obtained programmed death-ligand 1 (PD-L1) antibody conjugated gold nanoshelled poly(lactic-co-glycolic acid) (PLGA) nanocapsules (NCs) encapsulating doxorubicin (DOX) (DOX@PLGA@Au-PD-L1 NCs). PLGA NCs encapsulating DOX were prepared by a modified single-emulsion oil-in-water (O/W) solvent evaporation method, and gold nanoshells were formed on the surface by gold seed growth method, which were coupled with PD-L1 antibodies by carbodiimide method. The fabricated DOX@PLGA@Au-PD-L1 NCs exhibited promising contrast enhancement in vitro ultrasound imaging. Furthermore, DOX encapsulated in NCs displayed good pH-responsive and photo-triggered drug release properties. After irradiating 200 μg/mL NCs solution with a laser for 10 min, the solution temperature increased by nearly 23°C, indicating that the NCs had good photothermal conversion ability. The targeting experiments confirmed that the NCs had specific target binding ability to TNBC cells overexpressing PD-L1 molecules. Cell experiments exhibited that the agent significantly reduced the survival rate of TNBC cells through photochemotherapy combination therapy. As a multifunctional diagnostic agent, DOX@PLGA@Au-PD-L1 NCs could be used for ultrasound targeted contrast imaging and photochemotherapy combination therapy of TNBC cells, providing a promising idea for early diagnosis and treatment of TNBC.

Tools for a personalized tacrolimus dose adjustment in the follow-up of renal transplant recipients. Metabolizing phenotype according to CYP3A genetic polymorphisms versus concentration-dose ratio

BACKGROUND AND JUSTIFICATION

The strategy of the concentration-dose (C/D) approach and the different profiles of tacrolimus (Tac) according to the cytochrome P450 polymorphisms (CYPs) focus on the metabolism of Tac and are proposed as tools for the follow-up of transplant patients. The objective of this study is to analyse both strategies to confirm whether the stratification of patients according to the pharmacokinetic behaviour of C/D corresponds to the classification according to their CYP3A4/5 cluster metabolizer profile.

MATERIALS AND METHODS

425 kidney transplant patients who received Tac as immunosuppressive treatment have been included. The concentration/dose ratio (C/D) was used to divide patients in terciles and classify them according to their Tac metabolism rate (fast, intermediate, and slow). Based on CYP3A4 and A5 polymorphisms, patients were classified into 3 metabolizer groups: fast (CYP3A5*1 carriers and CYP34A*1/*1), intermediate (CYP3A5*3/3 and CYP3A4*1/*1) and slow (CYP3A5*3/*3 and CYP3A4*22 carriers).

RESULTS

When comparing patients included in each metabolizer group according to C/D ratio, 47% (65/139) of the fast metabolizers, 85% (125/146) of the intermediate and only 12% (17/140) of the slow also fitted in the homonym genotype group. Statistically lower Tac concentrations were observed in the fast metabolizers group and higher Tac concentrations in the slow metabolizers when compared with the intermediate group both in C/D ratio and polymorphisms criteria. High metabolizers required approximately 60% more Tac doses than intermediates throughout follow-up, while poor metabolizers required approximately 20% fewer doses than intermediates. Fast metabolizers classified by both criteria presented a higher percentage of times with sub-therapeutic blood Tac concentration values.

CONCLUSION

Determination of the metabolizer phenotype according to CYP polymorphisms or the C/D ratio allows patients to be distinguished according to their exposure to Tac. Probably the combination of both classification criteria would be a good tool for managing Tac dosage for transplant patients.

Hydrogen sulfide (H2S) metabolism: Unraveling cellular regulation, disease implications, and therapeutic prospects for precision medicine

Hydrogen sulfide (H2S), traditionally recognized as a noxious gas with a pungent odor, has emerged as a fascinating metabolite originating from proteinaceous foods. This review provides a comprehensive examination of H2S regulatory metabolism in cell. Dysregulation of cellular processes plays a pivotal role in the pathogenesis of numerous diseases. Recent development explores the chemistry of biosynthesis and degradation of H2S in cells. The consequences of dysregulation causing diseases and the emerging role of hydrogen sulfide (H2S) modulation as a promising therapeutic platform has not been explored much. These disturbances can manifest as oxidative stress, inflammation, and aberrant cellular signaling pathways, contributing to the development and progression of diseases such as cancer, cardiovascular disorders, neurodegenerative diseases, and diabetes. Hydrogen sulfide has gained recognition as a key player in cellular regulation. H2S is involved in numerous physiological processes, including vasodilation, inflammation control, and cytoprotection. Recent advances in research have focused on modulating H2S levels to restore cellular balance and mitigate disease progression. This approach involves both exogenous H2S donors and inhibitors of H2S -producing enzymes. By harnessing the versatile properties of H2S, researchers and clinicians may develop innovative therapies that address the root causes of dysregulation-induced diseases. As our understanding of H2S biology deepens, the potential for precision medicine approaches tailored to specific diseases becomes increasingly exciting, holding the promise of improved patient outcomes and a new era in therapeutics.

Smart Physical-Based Transdermal Drug Delivery System:Towards Intelligence and Controlled Release

Transdermal drug delivery systems based on physical principles have provided a stable, efficient, and safe strategy for disease therapy. However, the intelligent device with real-time control and precise drug release is required to enhance treatment efficacy and improve patient compliance. This review summarizes the recent developments, application scenarios, and drug release characteristics of smart transdermal drug delivery systems fabricated with physical principle. Special attention is paid to the progress of intelligent design and concepts in of physical-based transdermal drug delivery technologies for real-time monitoring and precise drug release. In addition, facing with the needs of clinical treatment and personalized medicine, the recent progress and trend of physical enhancement are further highlighted for transdermal drug delivery systems in combination with pharmaceutical dosage forms to achieve better transdermal effects and facilitate the development of smart medical devices. Finally, the next generation and future application scenarios of smart physical-based transdermal drug delivery systems are discussed, a particular focus in vaccine delivery and tumor treatment.

Gastrin-releasing peptide receptor as a theranostic target in breast cancer: a systematic scoping review

The gastrin-releasing peptide receptor (GRPR) is known to be overexpressed in breast cancer, making it a promising target for both imaging and therapy within a theranostic framework. Various radioligands targeting GRPR have undergone investigation in preclinical and clinical studies related to breast cancer. This systematic scoping review aimed to assess the current evidence on GRPR-targeted radioligands for diagnostic and therapeutic applications in breast cancer. The methodology followed the PRISMA-ScR protocol. The literature search was conducted in September 2023 and encompassed MEDLINE, Embase, Cochrane, and Scopus databases. We included original peer-reviewed studies focused on breast cancer patients or in vivo breast cancer models. Two reviewers performed the study selection process independently. Data were extracted, synthesized, and categorized into preclinical and clinical studies, further subdivided based on radioligand properties. A total of 35 original studies were included in the review, with three of them evaluating therapeutic outcomes. The results indicated that GRPR-radioantagonists are superior to GRPR-agonists, exhibiting preferable in vivo stability, rapid, specific tumor targeting, and enhanced retention. Both preclinical and clinical evaluations demonstrated renal excretion and high uptake in normal GRPR-expressing tissue, primarily the pancreas. A significant positive correlation was observed between GRPR and estrogen-receptor expression. In the clinical setting, GRPR-radioligands effectively detected primary tumors and, to a lesser extent, lymph node metastases. Moreover, GRPR-targeted radioantagonists successfully identified distant metastases originating from various sites in advanced metastatic disease, strongly correlated with positive estrogen receptor expression. Preclinical therapeutic evaluation of GRPR-radioligands labeled with lutetium-177 showed promising tumor responses, and none of the studies reported any observed or measured side effects, indicating a safe profile. In conclusion, the evidence presented in this review indicates a preference for GRPR-targeted antagonists over agonists, owing to their superior kinetics and promising diagnostic potential. Clinical assessments suggested diagnostic value for GRPR-targeted theranostics in breast cancer patients, particularly those with high estrogen receptor expression. Nevertheless, in the therapeutic clinical context, paying attention to the radiation dose administered to the pancreas and kidneys is crucial.

Insights into the management of penile squamous cell carcinoma: from conventional approaches to emerging novel therapies

INTRODUCTION

Penile squamous cell carcinoma (PSCC), a rare genitourinary cancer, is associated with poor outcomes due to limited treatment effectiveness, especially in advanced stages.

AREAS COVERED

While chemotherapy and/or surgery remain the standard of care, emerging therapies like immunotherapy, targeted therapy, and human papillomavirus (HPV) directed therapies show promise. Key to advancing treatment is understanding the immune microenvironment to gain insights into tumor resistance mechanisms and potential therapeutic targets. The scarcity of data on PSCC is a major obstacle in advancing research for this rare cancer.

EXPERT OPINION

Future research should prioritize collaborative efforts across various research centers and countries. Enhancing data sharing and pooling resources can lead to a more comprehensive understanding of PSCC, ultimately supporting the development of precision medicine strategies tailored to this specific cancer type. This collaborative approach is essential for making significant strides in PSCC treatment and care.

Regulating diagnosis-Molecular and regulatory sub-stratifications of lung cancer treatment

The sociology of diagnosis has shown that diagnosis not only serves to label the underlying cause of disease but also to provide access to services and resources. Elaborating on this double-affordance of diagnosis, this article examines how precision medicine reconfigures diagnosis as a label and as a process in regulatory and clinical settings. Reporting from an ethnographic case study of the introduction of immunotherapy for lung cancer, the paper unfolds the uncertainties involved in dissecting diagnosis into layers and examines the efforts and negotiations it takes to enable these layers to work both as clinical entities and regulative entities with the purpose of delineating access to treatment. I suggest that the work of subdividing diseases into molecularly defined categories for the purpose of delineating treatment-eligible populations can be labelled 'diagnostic sub-stratification' and argue that it is pertinent to understand the political capacity of this strategy. Diagnostic sub-stratification involves a push of diagnosis from the clinic 'up' into the regulatory system and 'out' into the laboratories, obscuring who is accountable for the diagnostic categories employed to define patients' treatment access.

Towards precision medicine of long-acting aripiprazole through population pharmacokinetic modelling

Population pharmacokinetic (popPK) models constitute a valuable tool for characterizing the pharmacokinetic properties of once-monthly long-acting injectable aripiprazole (LAI aripiprazole) and quantifying the sources of variability in drug exposure. Our aim is to develop a popPK model of both aripiprazole and its metabolite dehydro-aripiprazole in patients treated with LAI aripiprazole, and to personalize the dosing regimen of aripiprazole across different sub-groups of patients. This is a prospective study investigating the pharmacokinetics of LAI aripiprazole. A total of 93 patients were included, 21 for model development and 71 for external model evaluation. A one-compartment model with linear absorption and elimination adequately described both aripiprazole and dehydro-aripiprazole concentrations. The weight of the patients has been shown to be the factor that most influences the absorption. However, the metabolizing phenotype for CYP2D6 and the concomitant treatment with strong inhibitors of this cytochrome have been shown to be the covariates that most influence total drug exposure. This is the first popPK model developed for LAI aripiprazole that includes aripiprazole and its main active metabolite, dehydroaripiprazole. It provides a personalized dosage recommendation that maximizes the probability of achieving optimal therapeutic concentrations and minimizes the difficulties associated with trial-and-error therapeutic strategies carried out in clinical practice.

[Precision medicine in oncology]

Personalized oncology according to current practice is primarily based on tumor biology, which is translated into genomic biomarkers. Mutations in oncogenes and tumor suppressor genes are targeted by rationally designed drugs and, conversely, are used to inform tailored treatment strategies. Faster and cheaper technologies for DNA sequencing enable genomic medicine in a clinical routine setting. Genomic features, tumor biology and clinical implications are integrated into individual therapy recommendations by molecular tumor boards, which have been established at many cancer centers in Germany and worldwide throughout recent years. This article discusses the promises and limitations of genomics-centered precision oncology and highlights future avenues and alternative approaches to individualize cancer treatment.

[Precision medicine in infectious diseases]

Infectious medicine faces a variety of challenges, such as the increase in antibiotic resistance and the emergence and spread of infectious diseases fueled by climate change and globalization. Precision medicine can provide solutions to many of these challenges. Since an untargeted request for diagnostic tests can lead to test results without clinical relevance, which can increase the use of non-indicated antibiotics, the principle aimed at is: targeted diagnostics (the right test) and consideration of patient characteristics (the right person) to optimize management (the right action). At the same time, one must always decide whether empirical therapy must be immediately initiated, even if the results of the initiated diagnostics are not yet available. In addition, many new diagnostics as well as therapies have recently been developed for the rapid detection and more specific treatment of bacterial infections. Molecular genetic methods, which offer more rapid results than classical bacterial cultures, are gaining ground as new diagnostics. New therapeutics such as bacteriophages, antibodies or antibacterial peptides allow increasingly precise treatment of certain bacterial infections. Precision medicine will also play an increasingly important role in infectious medicine in the future.

Decision-making as discovery: Vetting clinical research in a leading precision oncology service

Based on fieldwork carried out at the Early Drug Development Service of a world-leading cancer institution, our study sheds lights on decision-making processes at the stage where decisions are made about which clinical trial to pursue and thus which experimental drugs will feed the growing pipeline of molecularly guided therapies and therapeutic strategies available to treating physicians. The paper shows how such collective decision-making practices by a translational research unit employ formal tools and ad hoc valuation strategies that interweave technical-scientific matters of concern with patient-oriented clinical ones, as part of the institutional assetization of biomedical knowledge production. In the process, decision-making practices in part define the conditions of possibility for the provision of care in what is increasingly becoming a 'clinic of variants.' They do so by reconfiguring on an evolving basis the socio-material ecosystem through which precision oncology is enacted as a rapidly evolving assemblage of patients, physicians, research and support staff, protocols, molecular markers, drugs and administrative components.

Precision Medicine in Nephrology: An Integrative Framework of Multidimensional Data in the Kidney Precision Medicine Project

Chronic kidney disease (CKD) and acute kidney injury (AKI) are heterogeneous syndromes defined clinically by serial measures of kidney function. Each condition possesses strong histopathologic associations, including glomerular obsolescence or acute tubular necrosis, respectively. Despite such characterization, there remains wide variation in patient outcomes and treatment responses. Precision medicine efforts, as exemplified by the Kidney Precision Medicine Project (KPMP), have begun to establish evolving, spatially anchored, cellular and molecular atlases of the cell types, states, and niches of the kidney in health and disease. The KPMP atlas provides molecular context for CKD and AKI disease drivers and will help define subtypes of disease that are not readily apparent from canonical functional or histopathologic characterization but instead are appreciable through advanced clinical phenotyping, pathomic, transcriptomic, proteomic, epigenomic, and metabolomic interrogation of kidney biopsy samples. This perspective outlines the structure of the KPMP, its approach to the integration of these diverse datasets, and its major outputs relevant to future patient care.

N-of-1 medicine

ABSTRACT

The fields of precision and personalised medicine have led to promising advances in tailoring treatment to individual patients. Examples include genome/molecular alteration-guided drug selection, single-patient gene therapy design and synergy-based drug combination development, and these approaches can yield substantially diverse recommendations. Therefore, it is important to define each domain and delineate their commonalities and differences in an effort to develop novel clinical trial designs, streamline workflow development, rethink regulatory considerations, create value in healthcare and economics assessments, and other factors. These and other segments are essential to recognise the diversity within these domains to accelerate their respective workflows towards practice-changing healthcare. To emphasise these points, this article elaborates on the concept of digital health and digital medicine-enabled N-of-1 medicine, which individualises combination regimen and dosing using a patient's own data. We will conclude with recommendations for consideration when developing novel workflows based on emerging digital-based platforms.

Artificial Intelligence: Exploring utility in detection and typing of fungus with futuristic application in fungal cytology

Artificial Intelligence (AI) is an emerging, transforming and revolutionary technology that has captured attention worldwide. It is translating research into precision oncology treatments. AI can analyse large or big data sets requiring high-speed specialized computing solutions. The data are big in terms of volume and multimodal with the amalgamation of images, text and structure. Machine learning has identified antifungal drug targets, and taxonomic and phylogenetic classification of fungi based on sequence analysis is now available. Real-time identification tools and user-friendly mobile applications for identifying fungi have been discovered. Akin to histopathology, AI can be applied to fungal cytology. AI has been fruitful in cytopathology of the thyroid gland, breast, urine and uterine cervical lesions. AI has a huge scope in fungal cytology and would certainly bear fruit with its accuracy, reproducibility and capacity for handling big data. The purpose of this systematic review was to highlight the AI's utility in detecting fungus and its typing with a special focus on future application in fungal cytology. We also touch upon the basics of AI in brief.

Precision Medicine for Whom? Public Health Outputs from "Genomics England" and "All of Us" to Make Up for Upstream and Downstream Exclusion

This paper problematizes the precision medicine approach embraced by the All of Us Research Program (US) and by Genomics England (UK) in terms of benefits distribution, by arguing that current "diversity and inclusion" efforts do not prevent exclusiveness, unless the framing and scope of the projects are revisited in public health terms. Grounded on document analysis and fieldwork interviews, this paper analyzes efforts to address potential patterns of exclusion upstream (from participating in precision medicine research) and downstream (from benefitting from precision medicine outputs). It argues that efforts for inclusion upstream are not corresponded downstream, and this unbalance jeopardizes the equitable capacities of the projects. It concludes that enhanced focus on socio-environmental determinants of health and aligned public health interventions as precision medicine outputs would be to the benefit of all and especially of those who are most at risk of (upstream as well as downstream) exclusion.

Enabling Personalized Medicine in Orthopaedic Surgery Through Artificial Intelligence: A Critical Analysis Review

» The application of artificial intelligence (AI) in the field of orthopaedic surgery holds potential for revolutionizing health care delivery across 3 crucial domains: (I) personalized prediction of clinical outcomes and adverse events, which may optimize patient selection, surgical planning, and enhance patient safety and outcomes; (II) diagnostic automated and semiautomated imaging analyses, which may reduce time burden and facilitate precise and timely diagnoses; and (III) forecasting of resource utilization, which may reduce health care costs and increase value for patients and institutions.» Computer vision is one of the most highly studied areas of AI within orthopaedics, with applications pertaining to fracture classification, identification of the manufacturer and model of prosthetic implants, and surveillance of prosthesis loosening and failure.» Prognostic applications of AI within orthopaedics include identifying patients who will likely benefit from a specified treatment, predicting prosthetic implant size, postoperative length of stay, discharge disposition, and surgical complications. Not only may these applications be beneficial to patients but also to institutions and payors because they may inform potential cost expenditure, improve overall hospital efficiency, and help anticipate resource utilization.» AI infrastructure development requires institutional financial commitment and a team of clinicians and data scientists with expertise in AI that can complement skill sets and knowledge. Once a team is established and a goal is determined, teams (1) obtain, curate, and label data; (2) establish a reference standard; (3) develop an AI model; (4) evaluate the performance of the AI model; (5) externally validate the model, and (6) reinforce, improve, and evaluate the model's performance until clinical implementation is possible.» Understanding the implications of AI in orthopaedics may eventually lead to wide-ranging improvements in patient care. However, AI, while holding tremendous promise, is not without methodological and ethical limitations that are essential to address. First, it is important to ensure external validity of programs before their use in a clinical setting. Investigators should maintain high quality data records and registry surveillance, exercise caution when evaluating others' reported AI applications, and increase transparency of the methodological conduct of current models to improve external validity and avoid propagating bias. By addressing these challenges and responsibly embracing the potential of AI, the medical field may eventually be able to harness its power to improve patient care and outcomes.

Discordance in Recommendation Between Next-Generation Sequencing Test Reports and Molecular Tumor Boards in India

PURPOSE

Accurate understanding of the genomic and transcriptomic data provided by next-generation sequencing (NGS) is essential for the effective utilization of precision oncology. Molecular tumor boards (MTBs) aim to translate the complex data in NGS reports into effective clinical interventions. Often, MTB treatment recommendations differ from those in the NGS reports. In this study, we analyze the discordance between these recommendations and the rationales behind the discordances, in a non-high-income setting, with international input to evaluate the necessity of MTB in clinical practice.

METHODS

We collated data from MTB that were virtually hosted in Chennai, India. We included patients with malignancies who had NGS reports on solid tissue or liquid biopsies, and excluded those with incomplete data. MTB forms and NGS reports of each clinical case were analyzed and evaluated for recommendation concordance. Concordance was defined as an agreement between the first recommendation in the MTB forms and the therapeutic recommendations suggested in the NGS report. Discordance was the absence of the said agreement. The rationales for discordance were identified and documented.

RESULTS

Seventy MTB reports were analyzed with 49 cases meeting the inclusion criteria. The recommendation discordance was 49% (24 of 49). Discordant recommendations were mainly due to low level of evidence for the drug (75% of cases).

CONCLUSION

The discordance between MTB and NGS vendor recommendations highlights the clinical utility of MTB. The educational experiences provided by this initiative are an example of how virtual academic collaborations can enhance patient care and provider education across geographic borders.

A neoteric annotation on the advances in combination therapy for Parkinson's disease: nanocarrier-based combination approach and future anticipation. Part II: nanocarrier design and development in focus

INTRODUCTION

The current treatment modalities available for Parkinson's disease (PD) prove inadequate due to the inherent constraints in effectively transporting bioactive compounds across the blood-brain barrier. The utilization of synergistic combinations of multiple drugs in conjunction with advanced nanotechnology, emerges as a promising avenue for the treatment of PD, offering potential breakthroughs in treatment efficacy, targeted therapy, and personalized medicine.

AREAS COVERED

This review provides a comprehensive analysis of the efficacy of multifactorial interventions for PD, simultaneously addressing the primary challenges of conventional therapies and highlighting how advanced technologies can help overcome these limitations. Part II focuses on the effectiveness of nanotechnology for improving pharmacokinetics of conventional therapies, through the synergistic use of dual or multiple therapeutic agents into a single nanoformulation. Significant emphasis is laid on the advancements toward innovative integrations, such as CRISPR/Cas9 with neuroprotective agents and stem cells, all effectively synergized with nanocarriers.

EXPERT OPINION

By using drug combinations, we can leverage their combined effects to enhance treatment efficacy and mitigate side effects through lower dosages. This article is meant to give nanocarrier-mediated co-delivery of drugs and the strategic incorporation of CRISPR/Cas9, either as an independent intervention or synergized with a neuroprotective agent.