Statistical considerations for preclinical studies

Interfacing data science with cell therapy manufacturing: where we are and where we need to be

Although several cell-based therapies have received FDA approval, and others are showing promising results, scalable, and quality-driven reproducible manufacturing of therapeutic cells at a lower cost remains challenging. Challenges include starting material and patient variability, limited understanding of manufacturing process parameter effects on quality, complex supply chain logistics, and lack of predictive, well-understood product quality attributes. These issues can manifest as increased production costs, longer production times, greater batch-to-batch variability, and lower overall yield of viable, high-quality cells. The lack of data-driven insights and decision-making in cell manufacturing and delivery is an underlying commonality behind all these problems. Data collection and analytics from discovery, preclinical and clinical research, process development, and product manufacturing have not been sufficiently utilized to develop a "systems" understanding and identify actionable controls. Experience from other industries shows that data science and analytics can drive technological innovations and manufacturing optimization, leading to improved consistency, reduced risk, and lower cost. The cell therapy manufacturing industry will benefit from implementing data science tools, such as data-driven modeling, data management and mining, AI, and machine learning. The integration of data-driven predictive capabilities into cell therapy manufacturing, such as predicting product quality and clinical outcomes based on manufacturing data, or ensuring robustness and reliability using data-driven supply-chain modeling could enable more precise and efficient production processes and lead to better patient access and outcomes. In this review, we introduce some of the relevant computational and data science tools and how they are being or can be implemented in the cell therapy manufacturing workflow. We also identify areas where innovative approaches are required to address challenges and opportunities specific to the cell therapy industry. We conclude that interfacing data science throughout a cell therapy product lifecycle, developing data-driven manufacturing workflow, designing better data collection tools and algorithms, using data analytics and AI-based methods to better understand critical quality attributes and critical-process parameters, and training the appropriate workforce will be critical for overcoming current industry and regulatory barriers and accelerating clinical translation.

Optimizing mesenchymal stem cell extracellular vesicles for chronic wound healing: Bioengineering, standardization, and safety

Chronic wounds represent a significant global burden, afflicting millions with debilitating complications. Despite standard care, impaired healing persists due to factors like persistent inflammation and impaired tissue regeneration. Mesenchymal stem cell (MSC)-derived extracellular vesicles (EVs) offer an innovative regenerative medicine approach, delivering stem cell-derived therapeutic cargo in engineered nanoscale delivery systems. This review examines pioneering bioengineering strategies to engineer MSC-EVs into precision nanotherapeutics for chronic wounds. Emerging technologies like CRISPR gene editing, microfluidic manufacturing, and biomimetic delivery systems are highlighted for their potential to enhance MSC-EV targeting, optimize therapeutic cargo enrichment, and ensure consistent clinical-grade production. However, key hurdles remain, including batch variability, rigorous safety assessment for potential tumorigenicity, immunogenicity, and biodistribution profiling. Crucially, collaborative frameworks harmonizing regulatory science with bioengineering and patient advocacy hold the key to expediting global clinical translation. By overcoming these challenges, engineered MSC-EVs could catalyze a new era of off-the-shelf regenerative therapies, restoring hope and healing for millions afflicted by non-healing wounds.

In vitro dissolution/permeation tools for amorphous solid dispersions bioavailability forecasting II: Comparison and mechanistic insights

Along with the increasing demand for complex formulations comes the need for appropriate in vitro methodologies capable of predicting their corresponding in vivo performance and the mechanisms controlling the drug release which can impact on in vivo drug absorption. In vitro dissolution-permeation (D/P) methodologies that can account for the effects of enabling formulations on the permeability of drugs are increasingly being used in performance ranking during early development stages. This work comprised the application of two different cell-free in vitro D/P setups: BioFLUX™ and PermeaLoop™ to evaluate the dissolution-permeation interplay upon drug release from itraconazole (ITZ)- HPMCAS amorphous solid dispersions (ASDs) of different drug loads. A solvent-shift approach was employed, from a simulated gastric environment to a simulated intestinal environment in the donor compartment. PermeaLoop™ was then combined with microdialysis sampling to separate the dissolved (free) drug from other species present in solution, like micelle-bound drug and drug-rich colloids, in real time. This setup was applied to clarify the mechanisms for drug release and permeation from these ASDs. In parallel, a pharmacokinetic study (dog model) was conducted to assess the drug absorption from these ASDs and to compare the in vivo results with the data obtained from each in vitro D/P setup, allowing to infer which would be the most adequate setup for ASD ranking. Even though both D/P systems resulted in the same qualitative ranking, BioFLUX™ overpredicted the difference between the in vivo AUC of two ASDs, whereas PermeaLoop™ permeation flux resulted in a good correlation with the AUC observed in pharmacokinetic studies (dog model) (R2 ≈ 0.98). Also, PermeaLoop™ combined with a microdialysis sampling probe clarified the mechanisms for drug release and permeation from these ASDs. It demonstrated that the free drug was the only driving force for permeation, while the drug-rich colloids kept permeation active for longer periods by acting as drug reservoirs and maintaining constant high levels of free drug in solution, which are then immediately able to permeate. Hence, the data obtained points BioFLUX™ and PermeaLoop™ applications to different momentums in the drug product development pipeline: while BioFLUX™, an automated standardized method, poses as a valuable tool for initial ASD ranking during the early development stages, PermeaLoop™ combined with microdialysis sampling allows to gain mechanistic understanding of the dissolution-permeation interplay, being crucial to fine tune and identify leading ASD candidates prior to in vivo testing.

Feasibility study of intraoperative pericardial fluid biomarkers and length of stay after cardiac surgery

Objective

Pericardial fluid biomarkers reflect the physiologic state of the myocardium. Previously, we showed a sustained increase in pericardial fluid biomarkers compared with blood in the 48 hours after cardiac surgery. We assess the feasibility of analyzing 9 common cardiac biomarkers from pericardial fluid collected during cardiac surgery and test a preliminary hypothesis of association between the most common biomarkers, troponin and brain natriuretic peptide, and length of stay after surgery.

Methods

We prospectively enrolled 30 patients aged 18 years or more undergoing coronary artery or valvular surgery. Patients with ventricular assist devices, atrial fibrillation surgery, thoracic aorta surgery, redo surgery, concomitant noncardiac surgery, and preoperative inotropic support were excluded. Before pericardial excision during surgery, a 1-cm pericardial incision was made to insert an 18-gauge catheter and collect 10 mL of pericardial fluid. Concentrations of 9 established biomarkers of cardiac injury or inflammation including brain natriuretic peptide and troponin were measured. Zero truncated Poisson regression adjusted for Society of Thoracic Surgery Preoperative Risk of Mortality tested for a preliminary association between pericardial fluid biomarkers and length of stay.

Results

Pericardial fluid was collected and pericardial fluid biomarkers resulted for all patients. Adjusted for Society of Thoracic Surgery risk, brain natriuretic peptide, and troponin were associated with increased intensive care unit and overall hospital length of stay.

Conclusions

In 30 patients, pericardial fluid was obtained and analyzed for cardiac biomarkers. Adjusting for Society of Thoracic Surgery risk, pericardial fluid troponin and brain natriuretic peptide were preliminarily associated with increased length of stay. Further investigation is needed to validate this finding and to investigate the potential clinical utility of pericardial fluid biomarkers.

Statistical practice and transparent reporting in the neurosciences: Preclinical motor behavioral experiments

Longitudinal and behavioral preclinical animal studies generate complex data, which may not be well matched to statistical approaches common in this literature. Analyses that do not adequately account for complexity may result in overly optimistic study conclusions, with consequences for reproducibility and translational decision-making. Recent work interrogating methodological shortcomings in animal research has not yet comprehensively investigated statistical shortcomings in the analysis of complex longitudinal and behavioral data. To this end, the current cross-sectional meta-research study rigorously reviewed published mouse or rat controlled experiments for motor rehabilitation in three neurologic conditions to evaluate statistical choices and reporting. Medline via PubMed was queried in February 2020 for English-language articles published January 1, 2017- December 31, 2019. Included were articles that used rat or mouse models of stroke, Parkinson’s disease, or traumatic brain injury, employed a therapeutic controlled experimental design to determine efficacy, and assessed at least one functional behavioral assessment or global evaluation of function. 241 articles from 99 journals were evaluated independently by a team of nine raters. Articles were assessed for statistical handling of non-independence, animal attrition, outliers, ordinal data, and multiplicity. Exploratory analyses evaluated whether transparency or statistical choices differed as a function of journal factors. A majority of articles failed to account for sources of non-independence in the data (74–93%) and/or did not analytically account for mid-treatment animal attrition (78%). Ordinal variables were often treated as continuous (37%), outliers were predominantly not mentioned (83%), and plots often concealed the distribution of the data (51%) Statistical choices and transparency did not differ with regards to journal rank or reporting requirements. Statistical misapplication can result in invalid experimental findings and inadequate reporting obscures errors. Clinician-scientists evaluating preclinical work for translational promise should be mindful of commonplace errors. Interventions are needed to improve statistical decision-making in preclinical behavioral neurosciences research.

Bioinspired In Vitro Brain Vasculature Model for Nanomedicine Testing Based on Decellularized Spinach Leaves

Animal testing is often criticized due to ethical issues and complicated translation of the results obtained to the clinical stage of drug development. Existing alternative models for nanopharmaceutical testing still have many limitations and do not significantly decrease the number of animals used. We propose a simple, bioinspired in vitro model for nanopharmaceutical drug testing based on the decellularized spinach leaf's vasculature. This system is similar to human arterioles and capillaries in terms of diameter (300-10 μm) and branching. The model has proven its suitability to access the maneuverability of magnetic nanoparticles, particularly those composed of Fe₃O₄. Moreover, the thrombosis has been recreated in the model's vasculature. We have tested and compared the effects of both a single-chain urokinase plasminogen activator (scuPA) and a magnetically controlled nanocomposite prepared by heparin-mediated cross-linking of scuPA with Fe₃O₄ nanoparticles. Compositions were tested both in static and flow conditions.

Data Management Schema Design for Effective Nanoparticle Formulation for Neurotherapeutics

Translation of nanotherapeutics from preclinical research to clinical application is difficult due to the complex and dynamic interaction space between the nanotherapeutic and the brain environment. To improve translation, increased insight into nanoformulation-brain interactions in preclinical research is necessary. We developed a nanoformulation-brain database and wrote queries to connect the complex physical, chemical, and biological features of neurotherapeutics based on experimental data. We queried the database to select nanoformulations based on specific physical characteristics that enable effective penetration within the brain, including size, polydispersity index, and zeta potential. Additionally, we demonstrate the ability to query the database to return select nanoformulation characteristics, including nanoformulation methodology or methodological variables such as surfactant, polymer, drug loading, and sonication times. Finally, we show the capacity of our database to produce correlations relating nanoparticle formulation parameters to biological outcomes, including nanotherapeutic impact on cell viability in cultured brain slices.

The metabolic signaling of the nucleoredoxin-like 2 gene supports brain function

The nucleoredoxin gene NXNL2 encodes for two products through alternative splicing, rod-derived cone viability factor-2 (RdCVF2) that mediates neuronal survival and the thioredoxin-related protein (RdCVF2L), an enzyme that regulates the phosphorylation of TAU. To investigate the link between NXNL2 and tauopathies, we studied the Nxnl2 knockout mouse (Nxnl2-/-). We established the expression pattern of the Nxnl2 gene in the brain using a Nxnl2 reporter mouse line, and characterized the behavior of the Nxnl2-/- mouse at 2 months of age. Additionally, long term potentiation and metabolomic from hippocampal specimens were collected at 2 months of age. We studied TAU oligomerization, phosphorylation and aggregation in Nxnl2-/- brain at 18 months of age. Finally, newborn Nxnl2-/- mice were treated with adeno-associated viral vectors encoding for RdCVF2, RdCVF2L or both and measured the effect of this therapy on long-term potential, glucose metabolism and late-onset tauopathy. Nxnl2-/- mice at 2 months of age showed severe behavioral deficiency in fear, pain sensitivity, coordination, learning and memory. The Nxnl2-/- also showed deficits in long-term potentiation, demonstrating that the Nxnl2 gene is involved in regulating brain functions. Dual delivery of RdCVF2 and RdCVF2L in newborn Nxnl2-/- mice fully correct long-term potentiation through their synergistic action. The expression pattern of the Nxnl2 gene in the brain shows a predominant expression in circumventricular organs, such as the area postrema. Glucose metabolism of the hippocampus of Nxnl2-/- mice at 2 months of age was reduced, and was not corrected by gene therapy. At 18-month-old Nxnl2-/- mice showed brain stigmas of tauopathy, such as oligomerization, phosphorylation and aggregation of TAU. This late-onset tauopathy can be prevented, albeit with modest efficacy, by recombinant AAVs administrated to newborn mice. The Nxnl2-/- mice have memory dysfunction at 2-months that resembles mild-cognitive impairment and at 18-months exhibit tauopathy, resembling to the progression of Alzheimer's disease. We propose the Nxnl2-/- mouse is a model to study multistage aged related neurodegenerative diseases. The NXNL2 metabolic and redox signaling is a new area of therapeutic research in neurodegenerative diseases.

Urokinase-type plasminogen activator promotes N-cadherin-mediated synaptic recovery in the ischemic brain

Urokinase-type plasminogen activator (uPA) is a serine proteinase that catalyzes the generation of plasmin on the cell surface and activates cell signaling pathways that promote remodeling and repair. Neuronal cadherin (NCAD) is a transmembrane protein that in the mature brain mediates the formation of synaptic contacts in the II/III and V cortical layers. Our studies show that uPA is preferentially found in the II/III and V cortical laminae of the gyrencephalic cortex of the non-human primate. Furthermore, we found that in murine cerebral cortical neurons and induced pluripotent stem cell (iPSC)-derived neurons prepared from healthy human donors, most of this uPA is associated with pre-synaptic vesicles. Our in vivo experiments revealed that in both, the gyrencephalic cortex of the non-human primate and the lissecephalic murine brain, cerebral ischemia decreases the number of intact synaptic contacts and the expression of uPA and NCAD in a band of tissue surrounding the necrotic core. Additionally, our in vitro data show that uPA induces the synthesis of NCAD in cerebral cortical neurons, and in line with these observations, intravenous treatment with recombinant uPA three hours after the onset of cerebral ischemia induces NCAD-mediated repair of synaptic contacts in the area surrounding the necrotic core.

Mouse Models of Lung Fibrosis

The drug discovery pipeline, from discovery of therapeutic targets through preclinical and clinical development phases, to an approved product by health authorities, is a time-consuming and costly process, where a lead candidates' success at reaching the final stage is rare. Although the time from discovery to final approval has been reduced over the last decade, there is still potential to further optimize and streamline the evaluation process of each candidate as it moves through the different development phases. In this book chapter, we describe our preclinical strategies and overall decision-making process designed to evaluate the tolerability and efficacy of therapeutic candidates suitable for patients diagnosed with fibrotic lung disease. We also describe the benefits of conducting preliminary discovery trials, to aid in the selection of suitable primary and secondary outcomes to be further evaluated and assessed in subsequent internal and external validation studies. We outline all relevant research methodologies and protocols routinely performed by our research group and hope that these strategies and protocols will be a useful guide for biomedical and translational researchers aiming to develop safe and beneficial therapies for patients with fibrotic lung disease.

Biomonitoring and Digital Data Technology as an Opportunity for Enhancing Animal Study Translation

The failure of animal studies to translate to effective clinical therapeutics has driven efforts to identify underlying cause and develop solutions that improve the reproducibility and translatability of preclinical research. Common issues revolve around study design, analysis, and reporting as well as standardization between preclinical and clinical endpoints. To address these needs, recent advancements in digital technology, including biomonitoring of digital biomarkers, development of software systems and database technologies, as well as application of artificial intelligence to preclinical datasets can be used to increase the translational relevance of preclinical animal research. In this review, we will describe how a number of innovative digital technologies are being applied to overcome recurring challenges in study design, execution, and data sharing as well as improving scientific outcome measures. Examples of how these technologies are applied to specific therapeutic areas are provided. Digital technologies can enhance the quality of preclinical research and encourage scientific collaboration, thus accelerating the development of novel therapeutics.

Reporting experimental studies on animals - The problems with translating of outcomes to clinical benefits. Methodological and statistical considerations: The example of pulmonary hypertension

The variability inherent in animal models and the methods used to define drug response can lead to highly divergent results when evaluating new drug candidates. Several guidelines exist for high-quality and comprehensive reporting of experiments with animals. The present survey makes a quantitative demonstration of whether compliance with good preclinical practice guidelines can affect the results and reduce risk of over- or underestimation of treatment benefit. This meta-analysis was performed on more than 400 animal studies concerning pulmonary hypertension, where a wide range of potential therapeutic agents have been recently positively assessed in preclinical experiments. The experiments were reviewed according to the selected methodological and statistical items being recommended to report in papers. A quantitative evaluation was performed of their impact on effect size, which defined the efficacy of particular drug candidates. In addition, the paper also examines whether the quality score calculated for the papers included in the analysis changed over the previous 25 years. In conclusion, some information in experimental studies is often missed or incomplete, which complicates the correct evaluation and comprehension of obtained results. This in turn could subsequently increase the potential hazards involved in translating positive experimental outcomes to possible clinical benefits in patients.

Effect of statins on amyloidosis in the rodent models of Alzheimer's disease: Evidence from the preclinical meta-analysis

INTRODUCTION

Previous studies have shown contrasting results in determining efficacy of statins against amyloid beta accumulation. The aim of this study was to assess the impact of statin in AD.

METHOD

We searched PubMed and Embase for relevant preclinical studies. A meta-analysis of the statin's efficacy on amyloidosis and cognitive impairment was performed. Also, stratified analysis was performed on several covariates including the type of statin used, gender and age of rodents and duration of statin therapy, to account for the reported heterogeneity in the results obtained. The study protocol was registered in PROSPERO (CRD42018102557).

RESULT

17 studies including 22 comparisons, containing a sample size of 446 rodents, participated in the meta-analysis of statin's effect on overall Aβ deposition. Although the effect of statin on overall Aβ deposition was found to be protective (p < 0.00001) but as we categorized the efficacy of statin on different Aβ species (soluble and insoluble Aβ40/42) and Aβ plaque load, we found that significance in the protection decreased. A stratified meta-analysis demonstrated a significant role in the duration of statin supplements and rodent's age on the heterogeneity of the results. Statin administered to rodents for the longest duration (>6 months) and younger rodents (<6 months of age) demonstrated significant efficacy of statin on Aβ deposition.

CONCLUSION

Statin showed reduction in Aβ level but stratified analysis revealed that this effect of statin was dependent on rodent's age and duration of the treatment.

Toward Better Reproducibility in Experimental Research on New Agents for Pulmonary Hypertension. An Analysis of Data from Four Hundred Animal Studies

PURPOSE

Pre-clinical data can provide a rationale for subsequent clinical trials and they are the first step in drug development; however, the therapeutic effect observed during animal studies does not necessarily translate to similar results in humans.

METHODS

Taking the example of pulmonary hypertension, the present study explores whether the methodological aspects of preclinical experiments can determine the final result.

RESULTS

The present paper describes a systematic analysis of 409 studies conducted on a variety of animal models to identify potential drug candidates for PH treatment; it explores the influence of various aspects of study design on the final outcome, e.g. type of animal model of PH, dosage schedules of tested agents, type of anesthesia, measurement of exercise intolerance or animal survival.

CONCLUSIONS

The animal models of PH used for pre-clinical studies are diverse and there are several methodological items within the established protocols that can determine the obtained result. Graphical abstract.

Perioperative Neurocognitive Disorder: State of the Preclinical Science

The purpose of this article is to provide a succinct summary of the different experimental approaches that have been used in preclinical postoperative cognitive dysfunction research, and an overview of the knowledge that has accrued. This is not intended to be a comprehensive review, but rather is intended to highlight how the many different approaches have contributed to our understanding of postoperative cognitive dysfunction, and to identify knowledge gaps to be filled by further research. The authors have organized this report by the level of experimental and systems complexity, starting with molecular and cellular approaches, then moving to intact invertebrates and vertebrate animal models. In addition, the authors' goal is to improve the quality and consistency of postoperative cognitive dysfunction and perioperative neurocognitive disorder research by promoting optimal study design, enhanced transparency, and "best practices" in experimental design and reporting to increase the likelihood of corroborating results. Thus, the authors conclude with general guidelines for designing, conducting and reporting perioperative neurocognitive disorder rodent research.

Out of Control? Managing Baseline Variability in Experimental Studies with Control Groups

Control groups are expected to show what happens in the absence of the intervention of interest (negative control) or the effect of an intervention expected to have an effect (positive control). Although they usually give results we can anticipate, they are an essential component of all experiments, both in vitro and in vivo, and fulfil a number of important roles in any experimental design. Perhaps most importantly they help you understand the influence of variables that you cannot fully eliminate from your experiment and thus include them in your analysis of treatment effects. Because of this it is essential that they are treated as any other experimental group in terms of subjects, randomisation, blinding, etc. It also means that in almost all cases, contemporaneous control groups are required. Historical and baseline control groups serve a slightly different role and cannot fully replace control groups run as an integral part of the experiment. When used correctly, a good control group not only validates your experiment; it provides the basis for evaluating the effect of your treatments.

Curation and analysis of clinical pathology parameters and histopathologic findings from eTOXsys, a large database project (eTOX) for toxicologic studies

Large data sharing projects amongst the pharmaceutical industry have the potential to generate new insights using data on a scale that has not been previously available. A retrospective analysis of the preclinical toxicology data collected as part of the eTOX project was conducted with the aim to provide background rates and treatment-related value analysis on both clinical pathology and histopathology datasets. Incorporated into this analysis was an extensive data consolidation task to standardise all data. Reference intervals for common clinical pathology parameters in rat and dog were generated, alongside background histopathology incidence rates in the liver, heart and kidney. Systematically applied decision thresholds allowed consistent relabelling of data points considered anomalous, and maximum fold change estimates. Relabelling of anomalous data points was conducted for the histopathology data using a Bayesian model to identify dose-dependent increases in pathologies. The results of this study allow: newly generated data to be analysed using the same methodology, rates and distributions to be used when building predictive dose-response models, and the possibility to correlate clinical pathology findings with concurrent histopathology findings. In the first half of this paper we discuss data curation, in the second half we report on the analytical methods and results.

Recommendations for design and conduct of preclinical in vivo studies of orthopedic device-related infection

Orthopedic device-related infection (ODRI), including both fracture-related infection (FRI) and periprosthetic joint infection (PJI), remain among the most challenging complications in orthopedic and musculoskeletal trauma surgery. ODRI has been convincingly shown to delay healing, worsen functional outcome and incur significant socio-economic costs. To address this clinical problem, ever more sophisticated technologies targeting the prevention and/or treatment of ODRI are being developed and tested in vitro and in vivo. Among the most commonly described innovations are antimicrobial-coated orthopedic devices, antimicrobial-loaded bone cements and void fillers, and dual osteo-inductive/antimicrobial biomaterials. Unfortunately, translation of these technologies to the clinic has been limited, at least partially due to the challenging and still evolving regulatory environment for antimicrobial drug-device combination products, and a lack of clarity in the burden of proof required in preclinical studies. Preclinical in vivo testing (i.e. animal studies) represents a critical phase of the multidisciplinary effort to design, produce and reliably test both safety and efficacy of any new antimicrobial device. Nonetheless, current in vivo testing protocols, procedures, models, and assessments are highly disparate, irregularly conducted and reported, and without standardization and validation. The purpose of the present opinion piece is to discuss best practices in preclinical in vivo testing of antimicrobial interventions targeting ODRI. By sharing these experience-driven views, we aim to aid others in conducting such studies both for fundamental biomedical research, but also for regulatory and clinical evaluation. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 37:271-287, 2019.

Reduction of Acquisition time using Partition of the sIgnal Decay in Spectroscopic Imaging technique (RAPID-SI)

To overcome long acquisition times of Chemical Shift Imaging (CSI), a new Magnetic Resonance Spectroscopic Imaging (MRSI) technique called Reduction of Acquisition time by Partition of the sIgnal Decay in Spectroscopic Imaging (RAPID-SI) using blipped phase encoding gradients inserted during signal acquisition was developed. To validate the results using RAPID-SI and to demonstrate its usefulness in terms of acquisition time and data quantification; simulations, phantom and in vivo studies were conducted, and the results were compared to standard CSI. The method was based upon the partition of a magnetic resonance spectroscopy (MRS) signal into sequential sub-signals encoded using blipped phase encoding gradients inserted during signal acquisition at a constant time interval. The RAPID-SI technique was implemented on a clinical 3 T Siemens scanner to demonstrate its clinical utility. Acceleration of data collection was performed by inserting R (R = acceleration factor) blipped gradients along a given spatial direction during data acquisition. Compared to CSI, RAPID-SI reduced acquisition time by the acceleration factor R. For example, a 2D 16x16 data set acquired in about 17 min with CSI, was reduced to approximately 2 min with the RAPID-SI (R = 8). While the SNR of the acquired RAPID-SI signal was lower compared to CSI by approximately the factor √R, it can be improved after data pre-processing and reconstruction. Compared to CSI, RAPID-SI reduces acquisition time, while preserving metabolites information. Furthermore, the method is flexible and could be combined with other acceleration methods such as Parallel Imaging.

The bench is closer to the bedside than we think: Uncovering the ethical ties between preclinical researchers in translational neuroscience and patients in clinical trials

Millions of people worldwide currently suffer from serious neurological diseases and injuries for which there are few, and often no, effective treatments. The paucity of effective interventions is, no doubt, due in large part to the complexity of the disorders, as well as our currently limited understanding of their pathophysiology. The bleak picture for patients, however, is also attributable to avoidable impediments stemming from quality concerns in preclinical research that often escape detection by research regulation efforts. In our essay, we connect the dots between these concerns about the quality of preclinical research and their potential ethical impact on the patients who volunteer for early trials of interventions informed by it. We do so in hopes that a greater appreciation among preclinical researchers of these serious ethical consequences can lead to a greater commitment within the research community to adopt widely available tools and measures that can help to improve the quality of research.

Efficient two-stage designs and proper inference for animal studies

Cost-effective yet efficient designs are critical to the success of animal studies. We propose a two-stage design for cost-effectiveness animal studies with continuous outcomes. Given the data from the two-stage design, we derive the exact distribution of the test statistic under null hypothesis to appropriately adjust for the design's adaptiveness. We further generalize the design and inferential procedure to the K-sample case with multiple comparison adjustment. We conduct simulation studies to evaluate the small sample behavior of the proposed design and test procedure. The results indicate that the proposed test procedure controls the type I error rate for the one-sample design and the family-wise error rate for K-sample design very well; whereas the naive approach that ignores the design's adaptiveness due to the interim look severely inflates the type I error rate or family-wise error rate. Compared with the standard one-stage design, the proposed design generally requires a smaller sample size.

Increasing efficiency of preclinical research by group sequential designs

Despite the potential benefits of sequential designs, studies evaluating treatments or experimental manipulations in preclinical experimental biomedicine almost exclusively use classical block designs. Our aim with this article is to bring the existing methodology of group sequential designs to the attention of researchers in the preclinical field and to clearly illustrate its potential utility. Group sequential designs can offer higher efficiency than traditional methods and are increasingly used in clinical trials. Using simulation of data, we demonstrate that group sequential designs have the potential to improve the efficiency of experimental studies, even when sample sizes are very small, as is currently prevalent in preclinical experimental biomedicine. When simulating data with a large effect size of d = 1 and a sample size of n = 18 per group, sequential frequentist analysis consumes in the long run only around 80% of the planned number of experimental units. In larger trials (n = 36 per group), additional stopping rules for futility lead to the saving of resources of up to 30% compared to block designs. We argue that these savings should be invested to increase sample sizes and hence power, since the currently underpowered experiments in preclinical biomedicine are a major threat to the value and predictiveness in this research domain.

A Bayesian multi-stage cost-effectiveness design for animal studies in stroke research

Much progress has been made in the area of adaptive designs for clinical trials. However, little has been done regarding adaptive designs to identify optimal treatment strategies in animal studies. Motivated by an animal study of a novel strategy for treating strokes, we propose a Bayesian multi-stage cost-effectiveness design to simultaneously identify the optimal dose and determine the therapeutic treatment window for administrating the experimental agent. We consider a non-monotonic pattern for the dose-schedule-efficacy relationship and develop an adaptive shrinkage algorithm to assign more cohorts to admissible strategies. We conduct simulation studies to evaluate the performance of the proposed design by comparing it with two standard designs. These simulation studies show that the proposed design yields a significantly higher probability of selecting the optimal strategy, while it is generally more efficient and practical in terms of resource usage.