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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Impact of Variability in Patient Exposure During Premarket Clinical Development on Postmarket Safety Outcomes

We characterized the size of the premarket safety population for 278 small-molecule new molecular entities (NMEs) and 61 new therapeutic biologics (NTBs) approved by the US Food and Drug Administration (FDA) between October 1, 2002, and December 31, 2014, evaluating the relationship of premarket safety population size to regulatory characteristics and postmarket safety outcomes. The median size of the safety population was 1,044, and was lower for NTBs than NMEs (median: 920 vs. 1,138, P = 0.04), orphan products than nonorphan products (393 vs. 1,606, P < 0.001), and for products with fast-track designation (617 vs. 1,455, P < 0.001), priority review (630 vs. 1,735, P < 0.001), and accelerated approval (475 vs. 1,164, P < 0.001), than products without that designation. The median number of postmarket safety label updates and issues added to the label were higher with larger premarket exposure among nonorphan products, but not among orphan products. Products with accelerated approval using a surrogate end point had a higher median number of safety issues added to the label than those with full approval, but this did not vary with the size of the safety population; fast-track and priority review were not associated with the number of safety issues added to the label. Here, a smaller safety population size was associated with a longer time to first safety outcome for nonorphan products but not orphan products. For orphan and nonorphan products combined, smaller premarket safety population size is not associated with the number or timing of postmarket safety outcomes, regardless of expedited program participation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Recommendations for Dose Selection for Adolescent Patients in Relevant Adult Oncology Clinical Trials

Our research supported the dose selection recommendations for adolescents in the US Food and Drug Administration (FDA) Guidance on Inclusion of Adolescent Patients in Adult Oncology Clinical Trials. The FDA Guidance states that for drugs administered as a flat dose in adults and data showing no clinically meaningful effect of body size on drug exposure and toxicity in adults, a minimum body weight threshold may need to be defined to prevent adolescents who have a lower body weight from exceeding adult exposures. Our review of adult population pharmacokinetic analyses of new molecular entities approved for oncology between January 2015 and March 2021 suggested that 40 kg (the approximate median body weight of a 12-year-old) is generally the lower end of the body weight range that has no clinically relevant effect on drug pharmacokinetics or safety. In conclusion, the minimum body weight threshold and selection of an appropriate dose for adolescents in relevant adult oncology clinical trials should ultimately be determined based on available data on pharmacokinetics or pharmacodynamics of the investigational drug with consideration of body size effect on drug exposure, toxicity, and efficacy data (if available), the therapeutic index of the drug, and dose- and exposure-response relationships in adults.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Extrapolation of Efficacy from Adults to Pediatric Patients of Drugs for Treatment of Partial Onset Seizures: A Regulatory Perspective

The US Food and Drug Administration (FDA) has concluded that the efficacy of drugs approved for the treatment of partial onset seizures (POS) in adults can be extrapolated to pediatric patients 1 month of age and above and that independent efficacy trials in this pediatric population are no longer needed. This paper focuses on the dosing, pharmacokinetic (PK), exposure‐response, and clinical information that were leveraged from the approved drugs for the treatment of POS to conduct analyses that supported extrapolation of efficacy in pediatric patients. Clinical data from trials for eight drugs (levetiracetam, oxcarbazepine, topiramate, lamotrigine, gabapentin, perampanel, tiagabine, and vigabatrin) approved in both adults and pediatric patients for the treatment of POS were analyzed. Comparisons of exposures at approved doses, placebo response, and model‐based exposure‐response relationships were performed. Based on disease similarity, similar response to intervention, and similar exposure‐response relationships in adults and pediatric patients, it was concluded that extrapolation of efficacy in pediatric patients aged 1 month and above is acceptable. PK analysis to determine pediatric dose and regimens that provide drug exposure similar to that known to be effective in adult patients with POS will be required, along with long‐term open‐label safety data in pediatric patients.

Pharmacology & Pharmacy↗
DOE OSTI2023

The Association Between Baseline Hepatic or Renal Function and Clinical Outcomes for Patients With Non–Small Cell Lung Cancer Treated With a PD –1/PD– L1 Blocking Antibody Using Real–World and Trial Data

Clinical trials have demonstrated the benefit of PD-1/PD-L1 blocking antibodies for the treatment of patients with advanced non-small cell lung cancer (NSCLC) in defined patient populations that often exclude patients with moderate or severe hepatic or renal impairment. We assessed the association between overall survival (OS) and baseline organ function in patients with advanced NSCLC treated with PD-1/PD-L1 blocking antibodies in real-world data (RWD; patient-level data from electronic health records) and pooled clinical trial data submitted to the US Food and Drug Administration (FDA). The Kaplan–Meier estimator was used to estimate OS in different subgroups based on organ function. Unadjusted and adjusted Cox proportional hazards models were used to estimate the association between OS and organ function. In this hypothesis-generating study, baseline renal impairment did not appear to be associated with OS, while patients with baseline liver impairment had shorter OS. RWD provided information on a broader range of renal and hepatic function than was evaluated in clinical trials and hold promise to complement trial data in better understanding populations not represented in clinical trials.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Methodology for Good Machine Learning with Multi‐Omics Data

In 2020, Novartis Pharmaceuticals Corporation and the U.S. Food and Drug Administration (FDA) started a 4‐year scientific collaboration to approach complex new data modalities and advanced analytics. The scientific question was to find novel radio‐genomics‐based prognostic and predictive factors for HR+/HER− metastatic breast cancer under a Research Collaboration Agreement. This collaboration has been providing valuable insights to help successfully implement future scientific projects, particularly using artificial intelligence and machine learning. This tutorial aims to provide tangible guidelines for a multi‐omics project that includes multidisciplinary expert teams, spanning across different institutions. We cover key ideas, such as “maintaining effective communication” and “following good data science practices,” followed by the four steps of exploratory projects, namely (1) plan, (2) design, (3) develop, and (4) disseminate. We break each step into smaller concepts with strategies for implementation and provide illustrations from our collaboration to further give the readers actionable guidance.

Pharmacology & Pharmacy↗
DOE OSTI2023

Addressing Coldwater Temperature Impairment in a Changing Climate

Climate change is concerning for fisheries professionals because increased water temperatures threaten coldwater habitats, which are vital to recreational and commercial fisheries and keystone species. The Clean Water Act provides a legal framework to identify and address water quality impairments including those associated with temperature. However, although this framework provides a basic strategy to identify impairments, develop total maximum daily loads, and reduce pollution, it does not explicitly consider the challenges of a changing climate in addressing water quality impairments. Clean Water Act administrators and fisheries professionals can facilitate temperature restoration planning and implementation using the Clean Water Act framework to link stakeholders to the management of coldwater resources. Stakeholder engagement and collaboration, robust local monitoring, and incorporating climate resilience into restoration planning and implementation will promote comprehensive management of temperature impairments and the effects of climate change on fisheries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Risk-based area of review estimation in overpressured reservoirs to support injection well storage facility permit requirements for CO 2 storage projects

This paper by the Energy & Environmental Research Center presents a workflow and modeling approach for delineating a risk-based area of review (AOR) to support a U.S. Environmental Protection Agency (EPA) Class VI permit for a carbon dioxide (CO 2 ) storage project. The approach combines semianalytical solutions for estimating formation fluid leakage through a hypothetical leaky wellbore with the results of numerical reservoir simulations to define the AOR. The modeling utilizes 1) semianalytical solutions from the peer-reviewed literature for formation fluid leakage through abandoned wellbores by Raven (1990) and Avci (1994), 2) a FORTRAN model compiled and described in Cihan et al. (2011, 2012) called ASLMA (Analytical Solution for Leakage in Multilayered Aquifers), and 3) a computational framework for estimating a risk-based AOR first proposed by Oldenburg et al. (2014, 2016). Therefore, the approach builds upon well-established research and underlying hydrogeological principles that have been upheld for nearly three decades. Moreover, the ASLMA model has been broadly applied to an array of storage projects. The work presented herein extends these earlier works using a custom wrapper written in the software environment, R (R Core Team, 2020), which was developed to perform multiple runs of the ASLMA model using given ranges for one or more input parameters. In addition, the current work simulates the pressure buildup within the storage reservoir in response to CO 2 injection using a compositional simulator to better accommodate the temporospatial evolution of pressure buildup within the storage reservoir that is more accurately modeled using a heterogeneous geologic model and a compositional simulator that accounts for the multiphase interactions. The workflow is demonstrated using a case study for a 180,000-metric-ton-per-year storage project located in the PCOR (Plains CO 2 Reduction) Partnership region. For the storage project evaluated here, under the scenario where the leaky wellbore is open to a saline aquifer (thief zone) between the overlying seal (cap rock) and the underground sources of drinking water (USDW), the risk-based AOR essentially collapses to the areal extent of the CO 2 plume in the storage reservoir because the pressure buildup in the storage reservoir beyond the CO 2 plume is insufficient to drive formation fluids up a hypothetical leaky wellbore into the USDW. However, even under the conservative assumption that the leaky wellbore is not open to a thief zone, beyond the areal extent of the CO 2 plume, the incremental leakage is less than 400 m 3 over 20 years, which represents ~0.0001% or less of the total volume of water contained within the USDW rock volume. As discussed in the text, the threshold criterion for defining the risk-based AOR is site-specific and should be informed by the results of the sensitivity analysis and available site characterization data. The approach outlined in this paper is designed to be protective of USDWs and, therefore, comply with the Safe Drinking Water Act requirements and provisions for the U.S. EPA Class VI Underground Injection Control (UIC) Program (Class VI Rule) and North Dakota Administrative Code Chapter 43-05-01.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Antibiotic Treatment Prior to Injury Abrogates the Detrimental Effects of LPS in STR/ort Mice Susceptible to Osteoarthritis Development

Post traumatic osteoarthritis (PTOA) is a form of secondary osteoarthritis (OA) that develops in ~50% of cases of severe articular joint injuries and leads to chronic and progressive degradation of articular cartilage and other joint tissues. PTOA progression can be exacerbated by repeated injury and systemic inflammation. Few studies have examined approaches for blunting or slowing down PTOA progression with emphasis on systemic inflammation; most arthritis studies focused on the immune system have been in the context of rheumatoid arthritis. To examine how the gut microbiome affects systemic inflammation during PTOA development, we used a chronic antibiotic treatment regimen starting at weaning for 6 weeks before anterior cruciate ligament (ACL) rupture in STR/ort mice combined with lipopolysaccharide (LPS)-induced systemic inflammation. STR/ort mice develop spontaneous OA as well as a more severe PTOA phenotype than C57Bl/6J mice. By 6 weeks post injury, histological examination showed a more robust cartilage staining in the antibiotic-treated (AB) STR/ort mice than in the untreated STR/ort controls. Furthermore, we also examined the effects of AB treatment on systemic inflammation and found that the effects of LPS administration before injury are also blunted by AB treatment in STR/ort mice. The AB- or AB+LPS-treated STR/ort injured joints more closely resembled the C57Bl/6J VEH OA phenotypes than the vehicle- or LPS-treated STR/ort, suggesting that antibiotic treatment has the potential to slow disease progression and should be further explored therapeutically as prophylactic post injury.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Sostdc1 Suppression in the Absence of Sclerostin Potentiates Anabolic Action of Cortical Bone in Mice

ABSTRACT The development of Wnt-based osteoanabolic agents has progressed rapidly in recent years, given the potent effects of Wnt modulation on bone homeostasis. Simultaneous pharmacologic inhibition of the Wnt antagonists sclerostin and Dkk1 can be optimized to create potentiated effects in the cancellous bone compartment. We looked for other candidates that might be co-inhibited along with sclerostin to potentiate the effects in the cortical compartment. Sostdc1 (Wise), like sclerostin and Dkk1, also binds and inhibits Lrp5/6 coreceptors to impair canonical Wnt signaling, but Sostdc1 has greater effects in the cortical bone. To test this concept, we deleted Sostdc1 and Sost from mice and measured the skeletal effects in cortical and cancellous compartments individually. Sost deletion alone produced high bone mass in all compartments, whereas Sostdc1 deletion alone had no measurable effects on either envelope. Mice with codeletion of Sostdc1 and Sost had high bone mass and increased cortical properties (bone mass, formation rates, mechanical properties), but only among males. Combined administration of sclerostin antibody and Sostdc1 antibody in wild-type female mice produced potentiation of cortical bone gain despite no effect of Sostdc1 antibody alone. In conclusion, Sostdc1 inhibition/deletion can work in concert with sclerostin deficiency to improve cortical bone properties. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

US FDA Postmarketing Requirements and Commitments: A Systematic Assessment of Clinical Pharmacology Studies and Their Impact on US FDA Prescribing Information

Abstract Many of the conditions for the safe and effective use of new molecular entities (NMEs) are understood at the time of initial drug approval. However, some remaining knowledge gaps can be addressed after drug approval through postmarketing requirements (PMRs) or commitments (PMCs) established by the US Food and Drug Administration (FDA). Our objective was to conduct an assessment of clinical pharmacology–related PMRs and PMCs established at the time of approval and evaluate the impact of fulfilled PMRs and PMCs on prescription information (PI). This analysis included clinical pharmacology–related PMRs and PMCs established for NMEs approved between 2009 and 2020. Of the 1171 PMRs and PMCs, over one‐third were clinical pharmacology–related. Of these, 46% were to evaluate drug interactions, 16% were to evaluate drug dosing in patients with hepatic impairment, and 10% were related to dose. The majority (57%) of PMRs and PMCs were fulfilled at the time of analysis, with a median time to fulfillment of approximately 2.3 years. The majority (94%) of the fulfilled PMRs and PMCs, either with or without a PI revision, resulted in new or modified instructions for use or supported existing instructions for use. This is the first time that clinical pharmacology–related PMRs and PMCs have been catalogued and analyzed to understand their impact on PI. An understanding of the knowledge gaps that exist at the time of drug approval could inform the most effective and efficient methods for evidence generation prior to and after new drug approval.

Pharmacology & Pharmacy↗
DOE OSTI2024

Statin Drug‐Drug Interactions: Pharmacokinetic Basis of FDA Labeling Recommendations and Comparison Across Common Tertiary Clinical Resources

Abstract Statins are widely prescribed and highly susceptible to pharmacokinetic (PK)‐based drug–drug interactions (DDIs). To date, there has not been a comprehensive analysis of the basis upon which statin DDI recommendations in US Food and Drug Administration (FDA) prescribing information (PI) are derived. We have conducted such an analysis. We also assessed the degree of concordance of statin DDI recommendations in FDA PI and those provided in common tertiary clinical resources. We catalogued statin DDI information, including PK data and management recommendations, for statin precipitant drugs approved from 2010 to 2021, available from FDA PI and tertiary clinical resource databases. Recommendations were categorized and mapped with associated PK data to assess consistency in the PK basis for labeling recommendations. From the 80 precipitant drugs evaluated, 180 statin DDIs were identified in FDA PI. Dedicated clinical DDI studies were conducted for 54% (n = 97) of these DDIs and 34% (n = 61) of DDI recommendations were extrapolated from clinical data with other statins. Overall, we found that PK‐based statin recommendations were consistent across PI. These findings highlight regulatory precedence for translating information across statins without conducting dedicated clinical DDI studies, which may support future efforts toward streamlining the approach to investigation and labeling of statin DDIs. In addition, with the exception of some notable discrepancies, general concordance was observed between FDA and tertiary resources regarding “Dose Adjustment” and “Avoid Coadministration” recommendations. However, further analyses are warranted across other DDI pairs to determine whether discordance can routinely lead to different clinical recommendations depending on the drug information resource.

Mease, James↗
DOE OSTI2021

BrazilClim : The overcoming of limitations of pre‐existing bioclimate data

Abstract Species distribution modelling has become instrumental in assessing the influence of environmental conditions on the occurrence or abundance of taxa. The set of environmental layers used for this purpose is a crucial aspect, for which different climate‐based (bioclimatic) datasets have been recently developed. These bioclimatic variables result from combinations of precipitation and temperatures surfaces. Here, we explored both the performance and possibility of improving some of the currently available bioclimatic databases, through an evaluation of the precipitation and temperatures surfaces used to generate them. For this purpose, we used a combination of statistic and graphic approaches. We focused on Brazil, not only due to its natural megadiversity, but also due to its continental size and orographic heterogeneity: an excellent ground for refining methods replicable elsewhere. We found a better match between the climatic data measured on‐field and Tropical Rainfall Measuring Mission (TRMM 3B43 v7) in the case of precipitation, and the surfaces provided by the National Oceanic and Atmospheric Administration (NOAA) in the case of temperatures, sources uncommonly used for species niche modelling. We gauge‐calibrated the best performing surfaces using machine‐learning algorithms and generated corrected surfaces that allowed us to create BrazilClim: a database of bioclimatic variables, based on improved primary surfaces, which will result in more assertive predicted distributions and more actual pictures of the species' ecological requirements for megadiverse Brazil, an approach replicable elsewhere. All primary and bioclimatic surfaces generated for this study may be freely downloaded.

Ramoni‐Perazzi, Paolo↗
DOE OSTI2020

Antihypertensive effect of quinoa protein under simulated gastrointestinal digestion and peptide characterization

Abstract BACKGROUND Quinoa protein is a potential source of bioactive peptides. Although some studies have demonstrated its angiotensin converting enzyme (ACE) inhibitory properties, research into its in vivo effect on blood‐pressure regulation and peptide characterization remains limited. RESULTS Quinoa protein hydrolyzate (QPH) was prepared by simulated gastrointestinal digestion. QPH lowered the systolic blood pressure (SBP) and diastolic blood pressure (DBP) in spontaneously hypertensive model rats (SHRs) from 2 h to10 h after oral administration, effectively controlling blood pressure in these SHRs. An in vitro study showed that QPH is capable of inhibiting ACE activity. This was attributed to the activity of a number of low‐molecular‐weight peptides. With relatively high scores predicted by PeptideRanker, three promising bioactive peptides, FHPFPR, NWFPLPR, and NIFRPF, were further studied and their ACE‐inhibition effects were confirmed with IC 50 values of 34.92, 16.77, and 32.40 μM, respectively. A molecular docking study provided insights into the binding of ACE with peptides, and revealed that the presence of specific amino acids in the peptide sequence (Pro, Phe, and Arg at the C‐terminal, and Asn at the N‐terminal) could contribute to the interaction between ACE and peptides. CONCLUSION These results demonstrated the potential of QPH for the management of hypertension, which indicates that it could be a good candidate for inclusion in functional foods to control high blood pressure. © 2020 Society of Chemical Industry

Guo, Huimin↗
DOE OSTI2022

Broccoli seed extract rich in polysaccharides and glucoraphanin ameliorates DSS ‐induced colitis via intestinal barrier protection and gut microbiota modulation in mice

Abstract BACKGROUND Broccoli has received widespread attention because of its anti‐inflammatory and antioxidant effects. The present study aimed to explore the composition of broccoli seed extract (BSE) and its effect on colitis induced by dextran sulfate sodium (DSS). RESULTS BSE mainly comprises glucoraphanin and polysaccharides composed of arabinose, galactose, glucose and mannose. Animal experiments suggested that BSE intervention effectively reversed body weight loss, suppressed the levels of proinflammatory interleukin‐6, tumor necrosis factor‐α and interleukin‐1β, and elevated the levels of anti‐inflammatory interleukin‐10 and the activities of superoxide dismutase and glutathione in DSS‐induced colitis mice. According to histopathologic and immunohistochemical analysis of colon tissue, BSE intervention may repair the intestinal barrier by upregulating mRNA levels and the expression of tight junction proteins (claudin‐1, occludin and zonula occludens‐1). Gas chromatography–mass spectrometry (MS) analysis demonstrated that cecal short‐chain fatty acids in mice with BSE administration were significantly increased compared with the model group. Sulforaphane and sulforaphane‐ N ‐acetylcysteine were only detected in BSE group mice by ultra‐performance liquid chromatography‐MS analysis. In addition, BSE intervention evidently increased the abundance of Alistipeds , Coriobacteriaceae UCG‐002 and Bifidobacterium and decreased the abundance of Escheichia‐Shinella , Lachnospiraceae others , Parabacteroides , Ruminococcaceae others and Turicibacter , which possibly promoted carbohydrate metabolism and short‐chain fatty acid production. CONCLUSION The present study aimed to elucidate the effect of BSE on colitis and found that BSE, as a novel food ingredient, has great potential for the improvement of colitis. © 2022 Society of Chemical Industry.

Wu, Jiaying↗
DOE OSTI2022

Computational models of direct and indirect X‐ray breast imaging detectors for in silico trials

Abstract Background To facilitate in silico studies that investigate digital mammography (DM) and breast tomosynthesis (DBT), models replicating the variety in imaging performance of the DM and DBT systems, observed across manufacturers are needed. Purpose The main purpose of this work is to develop generic physics models for direct and indirect detector technology used in commercially available systems, with the goal of making them available open source to manufacturers to further tweak and develop the exact in silico replicas of their systems. Methods We recently reported on an in silico version of the SIEMENS Mammomat Inspiration DM/DBT system using an open‐source GPU‐accelerated Monte Carlo x‐ray imaging simulation code (MC‐GPU). We build on the previous version of the MC‐GPU codes to mimic the imaging performances of two other Food and Drug Administration (FDA)‐approved DM/DBT systems, such as Hologic Selenia Dimensions (HSD) and the General Electric Senographe Pristina (GSP) systems. In this work, we developed a hybrid technique to model the optical spread and signal crosstalk observed in the GSP and HSD systems. MC simulations are used to track each x‐ray photon till its first interaction within the x‐ray detector. On the other hand, the signal spread in the x‐ray detectors is modeled using previously developed analytical equations. This approach allows us to preserve the modeling accuracy offered by MC methods in the patient body, while speeding up secondary carrier transport (either electron–hole pairs or optical photons) using analytical equations in the detector. The analytical optical spread model for the indirect detector includes the depth‐dependent spread and collection of optical photons and relies on a pre‐computed set of point response functions that describe the optical spread as a function of depth. To understand the capabilities of the computational x‐ray detector models, we compared image quality metrics like modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE), simulated with our models against measured data. Please note that the purpose of these comparisons with measured data would be to gauge if the model developed as part of this work could replicate commercially used direct and indirect technology in general and not to achieve perfect fits with measured data. Results We found that the simulated image quality metrics such as MTF, NNPS, and DQE were in reasonable agreement with experimental data. To demonstrate the imaging performance of the three DM/DBT systems, we integrated the detector models with the VICTRE pipeline and simulated DM images of a fatty breast model containing a spiculated mass and a calcium oxalate cluster. In general, we found that the images generated using the indirect model appeared more blurred with a different noise texture and contrast as compared to the systems with direct detectors. Conclusions We have presented computational models of three commercially available FDA‐approved DM/DBT systems, which implement both direct and indirect detector technology. The updated versions of the MC‐GPU codes that can be used to replicate three systems are available in open source format through GitHub.

Sengupta, Aunnasha↗
DOE OSTI2022

Improving Abundance Estimates of Spring–Summer Snake River Chinook Salmon for Fisheries Management

Abstract The Columbia River basin is home to a run of spring–summer Chinook Salmon Oncorhynchus tshawytscha that returns to the Snake River drainage of Idaho, Oregon, and Washington in the Pacific Northwest. Historically, the run was one of the more productive throughout the Columbia River basin. However, Snake River spring–summer Chinook Salmon have experienced declines in abundance due to overfishing, habitat degradation, and dams. Several stocks are listed as threatened under the U.S. Endangered Species Act and are supported by mitigation hatcheries funded by Idaho Power Company, the Lower Snake River Compensation Plan, and the Bonneville Power Administration. To maximize tribal and state harvest of returning hatchery adults, minimize impacts on wild fish, and ensure that enough hatchery fish return to meet broodstock needs, careful fisheries management is required. Since 2008, managers have used hatchery adults, PIT-tagged as juveniles and detected at Lower Granite Dam, to generate adult abundance estimates. In season, these estimates inform state and tribal harvest shares and ensure that broodstock needs are met. Postseason, they provide smolt-to-adult survival and return rates. Since 2012, parentage-based tagging (PBT) has provided an alternative method to estimate stock- and age-specific returns at Lower Granite Dam, since returning hatchery adults sampled at Lower Granite Dam can be assigned to their parents. We compared stock-specific abundance estimates between PIT- and PBT-derived methodologies for return years 2016–2019. Across all years, PIT tag estimates accounted for 65% of the PBT-based estimates at Lower Granite Dam across all age-groups and release sites combined. This underrepresentation across all groups equated to 49,833 fish that were not accounted for in PIT tag abundance estimates. It is clear that PBT-based estimates should aide in-season harvest management and postseason run reconstruction to avoid the known bias of estimates from PIT tags, especially during years of low returns when increased accuracy is critical.

Coykendall, D. Katharine (ORCID:0000000211482397)↗
DOE OSTI2020

A Novel Physiologically Based Model of Creatinine Renal Disposition to Integrate Current Knowledge of Systems Parameters and Clinical Observations

Creatinine is the most common clinical biomarker of renal function. As a substrate for renal transporters, its secretion is susceptible to inhibition by drugs, resulting in transient increase in serum creatinine and false impression of damage to kidney. Novel physiologically based models for creatinine were developed here and (dis)qualified in a stepwise manner until consistency with clinical data. Data from a matrix of studies were integrated, including systems data (common to all models), proteomics‐informed in vitro – in vivo extrapolation of all relevant transporter clearances, exogenous administration of creatinine (to estimate endogenous synthesis rate), and inhibition of different renal transporters (11 perpetrator drugs considered for qualification during creatinine model development and verification on independent data sets). The proteomics‐informed bottom‐up approach resulted in the underprediction of creatinine renal secretion. Subsequently, creatinine‐trimethoprim clinical data were used to inform key model parameters in a reverse translation manner, highlighting best practices and challenges for middle‐out optimization of mechanistic models.

Scotcher, Daniel↗
DOE OSTI2022

Quantitative methods and modeling to assess COVID–19–interrupted in vivo pharmacokinetic bioequivalence studies with two reference batches

The coronavirus disease 2019 (COVID-19) has presented unprecedented challenges to the generic drug development, including interruptions in bioequivalence (BE) studies. Per guidance published by the US Food and Drug Administration (FDA) during the COVID-19 public health emergency, any protocol changes or alternative statistical analysis plan for COVID-19-interrupted BE study should be accompanied with adequate justifications and not lead to biased equivalence determination. In this study, we used a modeling and simulation approach to assess the potential impact of study outcomes when two different batches of a Reference Standard (RS) were to be used in an in vivo pharmacokinetic BE study due to the RS expiration during the COVID-19 pandemic. Simulations were performed with hypothetical drugs under two scenarios: (1) uninterrupted study using a single batch of an RS, and (2) interrupted study using two batches of an RS. The acceptability of BE outcomes was evaluated by comparing the results obtained from interrupted studies with those from uninterrupted studies. The simulation results demonstrated that using a conventional statistical approach to evaluate BE for COVID-19-interrupted studies may be acceptable based on the pooled data from two batches. An alternative statistical method which includes a “batch” effect to the mixed effects model may be used when a significant “batch” effect was found in interrupted four-way crossover studies. However, such alternative method is not applicable for interrupted two-way crossover studies. Overall, the simulated scenarios are only for demonstration purpose, the acceptability of BE outcomes for the COVID19-interrupted studies could be case-specific.

60 APPLIED LIFE SCIENCES↗