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NASA NTRS1991

Cooperative research and development opportunities with the National Cancer Institute

The Office of Technology Development (OTD) of the National Cancer Institute (NCI) is responsible for negotiating Cooperative Research and Development Agreements (CRADAs), whereby the knowledge resulting from NCI investigators' government-sponsored research is developed in collaboration with universities and/or industry into new products of importance for the diagnosis and treatment of cancer and acquired immunodeficiency syndrome (AIDS). The NCI has recently executed a unique 'clinical trials' CRADA and is developing a model agreement based upon it for the development and commercialization of products for the diagnosis and treatment of cancer and AIDS. NCI drug screening, preclinical testing, clinical trials, and AIDS program capabilities form the basis for this new technology development/technology transfer vehicle. NCI's extensive drug screening program and 'designer foods' program serve as potential sources of investigational new drugs (INDs) and cancer preventatives. Collaborations between NCI and pharmaceutical companies having the facilities, experience, and expertise necessary to develop INDs into approved drugs available to the public are being encouraged where the companies have proprietary rights to INDs, or where NCI has proprietary rights to INDs and invites companies to respond to a collaborator announcement published in the Federal Register. The joint efforts of the NCI and the chosen collaborator are designed to generate the data necessary to obtain pharmaceutic regulatory approval from the Food and Drug Administration (FDA) to market the drugs developed, and thereby make them available to health care providers for the diagnosis and treatment of cancer and AIDS.

Sybert, Kathleen↗

NASA NTRS2014

Pharmacokinetic Modeling of Intranasal Scopolamine in Plasma Saliva and Urine

Wu, L.↗

NASA NTRS2014

Pharmacokinetic Modeling of Intranasal Scopolamine in Plasma Saliva and Urine

An intranasal gel formulation of scopolamine (INSCOP) was developed for the treatment of Space Motion Sickness. The bioavailability and pharmacokinetics (PK) were evaluated under the Food and Drug Administration guidelines for clinical trials for an Investigative New Drug (IND). The aim of this project was to develop a PK model that can predict the relationship between plasma, saliva and urinary scopolamine concentrations using data collected from the IND clinical trial with INSCOP. METHODS: Twelve healthy human subjects were administered three dose levels (0.1, 0.2 and 0.4 mg) of INSCOP. Serial blood, saliva and urine samples were collected between 5 min to 24 h after dosing and scopolamine concentrations measured by using a validated LC-MS-MS assay. Pharmacokinetic Compartmental models, using actual dosing and sampling times, were built using Phoenix (version 1.2). Model discrimination was performed, by minimizing the Akaike Information Criteria (AIC), maximizing the coefficient of determination (r²) and by comparison of the quality of fit plots. RESULTS: The best structural model to describe scopolamine disposition after INSCOP administration (minimal AIC =907.2) consisted of one compartment for plasma, saliva and urine respectively that were inter-connected with different rate constants. The estimated values of PK parameters were compiled in Table 1. The model fitting exercises revealed a nonlinear PK for scopolamine between plasma and saliva compartments for K21, Vmax and Km. CONCLUSION: PK model for INSCOP was developed and for the first time it satisfactorily predicted the PK of scopolamine in plasma, saliva and urine after INSCOP administration. Using non-linear PK yielded the best structural model to describe scopolamine disposition between plasma and saliva compartments, and inclusion of non-linear PK resulted in a significant improved model fitting. The model can be utilized to predict scopolamine plasma concentration using saliva and/or urine data that allows non-invasive assessment of pharmacotherapeutics of scopolamine in space and other remote environments without requiring blood sampling.

Wu, L.↗

DOE OSTI2020

Solution Chemistry of Copper(II) Binding to Substituted 8-Hydroxyquinolines

8-Hydroxyquinolines (8HQs) are a family of lipophilic metal ion chelators that have been used in a range of analytical and pharmaceutical applications over the last 100 years. More recently, CQ (clioquinol; 5-chloro-7-iodo-8-hydroxyquinoline) and PBT2 (5,7-dichloro-2-[(dimethylamino)methyl]-8-hydroxyquinoline) have undergone clinical trials for the treatment of Alzheimer’s disease and Huntington’s disease. Because CQ and PBT2 appear to redistribute metals into cells, these compounds have been redefined as copper and zinc ionophores. Despite the attention surrounding the clinical trials and the clear link between 8HQs and metals, the fundamental solution chemistry of how these compounds bind divalent metals such as copper and zinc, as well as their mechanism(s) of action in mammalian systems, remains poorly understood. Here, we used a combination of X-ray absorption spectroscopy (XAS), high-energy resolution fluorescence detected (HERFD) XAS, electron paramagnetic resonance (EPR), and UV–visible absorption spectroscopies to investigate the aqueous solution chemistry of a range of 8HQ derivatives. To circumvent the known solubility issues with 8HQ compounds and their complexes with Cu(II), and to avoid the use of abiological organic solvents, we have devised a surfactant buffer system to investigate these Cu(II) complexes in aqueous solution. Our study comprises the first comprehensive investigation of the Cu(II) complexes formed with many 8HQs of interest in aqueous solution, and it provides the first structural information on some of these complexes. We find that halogen substitutions in 8HQ derivatives appear to have little effect on the Cu(II) coordination environment; 5,7-dihalogenated 8HQ conformers all have a pseudo square planar Cu(II) bound by two quinolin-8-olate anions, in agreement with previous studies. Conversely, substituents in the 2-position of the 8HQ moiety appear to cause significant distortions from the typical square-planar-like coordination of most Cu(II)-bis-8HQ complexes, such that the 8HQ moieties in the Cu(II)-bis-8HQ complex are rotated approximately 30–40° apart in a “propeller-like” arrangement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2014

A Population Pharmacokinetic Model for Disposition in Plasma, Saliva and Urine of Scopolamine after Intranasal Administration to Healthy Human Subjects

An intranasal gel formulation of scopolamine (INSCOP) was developed for the treatment of Space Motion Sickness. The bioavailability and pharmacokinetics (PK) were evaluated under the Food and Drug Administration guidelines for clinical trials with an Investigative New Drug (IND) protocol. The aim of this project was to develop a PK model that can predict the relationship between plasma, saliva and urinary scopolamine concentrations using data collected from the IND clinical trials with INSCOP. Methods: Twelve healthy human subjects were administered three dose levels (0.1, 0.2 and 0.4 mg) of INSCOP. Serial blood, saliva and urine samples were collected between 5 min and 24 h after dosing and scopolamine concentrations were measured by using a validated LC‐MS‐MS assay. Pharmacokinetic Compartmental models, using actual dosing and sampling times, were built using Phoenix (version 1.2). Model selection was based on the likelihood ratio test on the difference of criteria (‐2LL) and comparison of the quality of fit plots. Results: The best structural model for INSCOP (minimal ‐2LL= 502.8) was established. It consisted of one compartment each for plasma, saliva and urine, respectively, which were connected with linear transport processes except the nonlinear PK process from plasma to saliva compartment. The best‐fit estimates of PK parameters from individual PK compartmental analysis and Population PK model analysis were shown in Tables 1 and 2, respectively. Conclusion: A population PK model that could predict population and individual PK of scopolamine in plasma, saliva and urine after dosing was developed and validated. Incorporating a non‐linear transfer from plasma to saliva compartments resulted in a significantly improved model fitting. The model could be used to predict scopolamine plasma concentrations from salivary and urinary drug levels, allowing non‐invasive therapeutic monitoring of scopolamine in space and other remote environments.

Wu, L.↗

DOE OSTI2019

Niacin for Parkinson's disease

Abstract Parkinson's disease (PD) is a neurodegenerative disease associated with progressive loss of motor function and cognitive decline occurring in 1% of the USA population. There is no cure for PD, and current treatment regimens are directed towards treating symptoms and not treating the underlying cause of the disease. Chronic neuroinflammation is associated with loss of neuronal cells, leading to motor and cognitive decline. Current clinical trials on drugs and nutraceuticals, such as coenzyme Q10 and niacin, are being carried out to delay progression and reduce damage by inflammatory molecules, such as reactive oxygen species and cytokines, in PD patients. In this review, we present available clinical trials and the role of niacin in reducing neuroinflammation in PD.

Seamon, Marissa↗

DOE OSTI2021

Informing selection of drugs for COVID-19 treatment through adverse events analysis

Coronavirus disease 2019 (COVID-19) is an ongoing pandemic and there is an urgent need for safe and effective drugs for COVID-19 treatment. Since developing a new drug is time consuming, many approved or investigational drugs have been repurposed for COVID-19 treatment in clinical trials. Therefore, selection of safe drugs for COVID-19 patients is vital for combating this pandemic. Our goal was to evaluate the safety concerns of drugs by analyzing adverse events reported in post-market surveillance. We collected 296 drugs that have been evaluated in clinical trials for COVID-19 and identified 28,597,464 associated adverse events at the system organ classes (SOCs) level in the FDA adverse events report systems (FAERS). We calculated Z-scores of SOCs that statistically quantify the relative frequency of adverse events of drugs in FAERS to quantitatively measure safety concerns for the drugs. Analyzing the Z-scores revealed that these drugs are associated with different significantly frequent adverse events. Our results suggest that this safety concern metric may serve as a tool to inform selection of drugs with favorable safety profiles for COVID-19 patients in clinical practices. Caution is advised when administering drugs with high Z-scores to patients who are vulnerable to associated adverse events.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Development and validation of a mathematical model of heart rate response to fluid perturbation

Physiological closed-loop controlled (PCLC) medical devices monitor and automatically adjust the patient’s condition by using physiological variables as feedback, ideally with minimal human intervention to achieve the target levels set by a clinician. PCLC devices present a challenge when it comes to evaluating their performance, where conducting large clinical trials can be expensive. Virtual physiological patients simulated by validated mathematical models can be utilized to obtain preclinical evidence of safety and assess the performance of the PCLC medical device during normal and worst-case conditions that are unlikely to happen in a limited clinical trial. A physiological variable that plays a major role during fluid resuscitation is heart rate (HR). For in silico assessment of PCLC medical devices regarding fluid perturbation, there is currently no mathematical model of HR validated in terms of its predictive capability performance. This paper develops and validates a mathematical model of HR response using data collected from sheep subjects undergoing hemorrhage and fluid infusion. The model proved to be accurate in estimating the HR response to fluid perturbation, where averaged between 21 calibration datasets, the fitting performance showed a normalized root mean square error (NRMSE) of 7.41 ± 2.8%. The model was also evaluated in terms of model predictive capability performance via a leave-one-out procedure (21 subjects) and an independent validation dataset (6 subjects). Two different virtual cohort generation tools were used in each validation analysis. The generated envelope of virtual subjects robustly met the defined acceptance criteria, in which 95% of the testing datasets presented simulated HR patterns that were within a deviation of 50% from the observed data. In addition, out of 16000 and 18522 simulated subjects for the leave one-out and independent datasets, the model was able to generate at least one virtual subject that was close to the real subject within an error margin of 9.56 ± 3.15% and 11.1 ± 1.22% NRMSE, respectively. In conclusion, the model can generate valid virtual HR physiological responses to fluid perturbation and be incorporated into future non-clinical simulated testing setups for assessing PCLC devices intended for fluid resuscitation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Modeling resistance to the broadly neutralizing antibody PGT121 in people living with HIV-1

PGT121 is a broadly neutralizing antibody in clinical development for the treatment and prevention of HIV-1 infection via passive administration. PGT121 targets the HIV-1 V3-glycan and demonstrated potent antiviral activity in a phase I clinical trial. Resistance to PGT121 monotherapy rapidly occurred in the majority of participants in this trial with the sampled rebound viruses being entirely resistant to PGT121 mediated neutralization. However, two individuals experienced long-term ART-free viral suppression following antibody infusion and retained sensitivity to PGT121 upon viral rebound. Here, we develop mathematical models of the HIV-1 dynamics during this phase I clinical trial. We utilize these models to understand the dynamics leading to PGT121 resistance and to identify the mechanisms driving the observed long-term viral control. Our modeling highlights the importance of the relative fitness difference between PGT121 sensitive and resistant subpopulations prior to treatment. Specifically, by fitting our models to data, we identify the treatment-induced competitive advantage of previously existing or newly generated resistant population as a primary driver of resistance. Finally, our modeling emphasizes the high neutralization ability of PGT121 in both participants who exhibited long-term viral control.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

The progeria research foundation 10 th international scientific workshop; researching possibilities, ExTENding lives – webinar version scientific summary

Progeria is an ultra-rare (prevalence 1 in 20 million), fatal, pediatric autosomal dominant premature aging disease caused by a mutation in the LMNA gene. This mutation results in accumulation of a high level of an aberrant form of the nuclear membrane protein, Lamin A. This aberrant protein, termed progerin, accumulates in many tissues and is responsible for the diverse array of disease phenotypes. Children die predominantly from premature atherosclerotic cardiovascular disease. The Progeria Research Foundation’s 10th International Scientific Workshop took place via webinar on November 2 and 3, 2020. Participants from 30 countries joined in this new, virtual meeting format. Patient family presentations led the program, followed by updates on Progeria’s first-ever application for FDA drug approval as well as initial results from the only current Progeria clinical trial. This was followed by presentations of unpublished preclinical data on drugs in development targeting the disease-causing DNA mutation, the aberrant mRNA, progerin protein, and its downstream effector proteins. Tying bench to bedside, clinicians presented new discoveries on the natural history of disease to inform future clinical trial development and new Progeria aortic valve replacement procedures. The program engaged the Progeria research community as a single unit with a common goal – to treat and cure children with Progeria worldwide.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

In silico trials predict that combination strategies for enhancing vesicular stomatitis oncolytic virus are determined by tumor aggressivity

Background Immunotherapies, driven by immune-mediated antitumorigenicity, offer the potential for significant improvements to the treatment of multiple cancer types. Identifying therapeutic strategies that bolster antitumor immunity while limiting immune suppression is critical to selecting treatment combinations and schedules that offer durable therapeutic benefits. Combination oncolytic virus (OV) therapy, wherein complementary OVs are administered in succession, offer such promise, yet their translation from preclinical studies to clinical implementation is a major challenge. Overcoming this obstacle requires answering fundamental questions about how to effectively design and tailor schedules to provide the most benefit to patients. Methods We developed a computational biology model of combined oncolytic vaccinia (an enhancer virus) and vesicular stomatitis virus (VSV) calibrated to and validated against multiple data sources. We then optimized protocols in a cohort of heterogeneous virtual individuals by leveraging this model and our previously established in silico clinical trial platform. Results Enhancer multiplicity was shown to have little to no impact on the average response to therapy. However, the duration of the VSV injection lag was found to be determinant for survival outcomes. Importantly, through treatment individualization, we found that optimal combination schedules are closely linked to tumor aggressivity. We predicted that patients with aggressively growing tumors required a single enhancer followed by a VSV injection 1 day later, whereas a small subset of patients with the slowest growing tumors needed multiple enhancers followed by a longer VSV delay of 15 days, suggesting that intrinsic tumor growth rates could inform the segregation of patients into clinical trials and ultimately determine patient survival. These results were validated in entirely new cohorts of virtual individuals with aggressive or non-aggressive subtypes. Conclusions Based on our results, improved therapeutic schedules for combinations with enhancer OVs can be studied and implemented. Our results further underline the impact of interdisciplinary approaches to preclinical planning and the importance of computational approaches to drug discovery and development.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

A Pentavalent HIV-1 Subtype C Vaccine Containing Computationally Selected gp120 Strains Improves the Breadth of V1V2 Region Responses

Background: HIV-1 envelope (Env) variable loops 1 and 2 (V1V2) directed non-neutralizing antibodies were a correlate of decreased transmission risk in the RV144 vaccine trial. Thus, the elicitation and breadth of antibody responses against the V1V2 of HIV-1 Env are important considerations for HIV-1 vaccine candidates. The V1V2 region’s highly variable nature and the extensive diversity of subtype C HIV-1 Envelopes (Envs) make the V1V2 response breadth a high priority for HIV-1 vaccine regimens aiming for V1V2-mediated protection in Southern Africa. Here, we determined whether the breadth of the anti-V1V2 vaccine response can be broadened by including HIV-1 Env strains computationally designed to enhance the coverage of subtype C V1V2 sequence diversity. Methods: Three subtype C Env strains were selected to maximize antibody binding coverage while complementing subtype C vaccine gp120s that were given in human clinical trials in South Africa, as well as to improve epitope accessibility. Humoral immunogenicity of a novel trivalent gp120 vaccine immunogen, a bivalent gp120 boost already in clinical trials (1086C and TV1), and a pentavalent (all five gp120s combined) were evaluated in a preclinical immunization study in guinea pigs. The pentavalent combination was further evaluated with alum versus glucopyranosyl lipid adjuvants formulated in squalene-in-water emulsion (GLA-SE) adjuvants in non-human primates. The breadth of the anti-V1V2 response was assessed using an array of cross-subtype variable loops 1&2 (V1V2) scaffold proteins and linear V2 peptides. Results: The breadth of the IgG response against V1V2 antigens of the trivalent and pentavalent groups was comparable, and both were greater than the breadth of the bivalent group. Linear epitope mapping showed that two linear epitopes in V2 were targeted by the vaccinated animals: the V2 hotspot focused at 169K that potentially correlated with decreased HIV-1 risk in RV144 and the V2.2 site (179LDV/I181) that is part of the integrin α4β7 binding site. The bivalent vaccine elicited a significantly higher magnitude of binding to the V2 hotspot compared to the trivalent vaccine whereas the trivalent vaccine elicited significantly higher binding to the V2.2 epitope compared to the bivalent vaccine, while the pentavalent recognized both regions. Conclusions: These results demonstrate that the three new computationally selected subtype C Envs successfully complemented 1086C and TV1 for broader V1V2 antibody responses, and, in concert with adjuvants that stimulate V1V2 responses, can be considered as part of a rationale immunogen design to improve V1V2 IgG coverage in future vaccine trials in South Africa.

Immunology↗

DOE OSTI2021

Supervised learning with word embeddings derived from PubMed captures latent knowledge about protein kinases and cancer

Abstract Inhibiting protein kinases (PKs) that cause cancers has been an important topic in cancer therapy for years. So far, almost 8% of >530 PKs have been targeted by FDA-approved medications, and around 150 protein kinase inhibitors (PKIs) have been tested in clinical trials. We present an approach based on natural language processing and machine learning to investigate the relations between PKs and cancers, predicting PKs whose inhibition would be efficacious to treat a certain cancer. Our approach represents PKs and cancers as semantically meaningful 100-dimensional vectors based on word and concept neighborhoods in PubMed abstracts. We use information about phase I-IV trials in ClinicalTrials.gov to construct a training set for random forest classification. Our results with historical data show that associations between PKs and specific cancers can be predicted years in advance with good accuracy. Our tool can be used to predict the relevance of inhibiting PKs for specific cancers and to support the design of well-focused clinical trials to discover novel PKIs for cancer therapy.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Favipiravir Flow Synthesis

Researchers at Los Alamos have invented a novel flow/batch chemistry synthetic process to produce the small molecule anti-viral favipiravir more cheaply and rapidly to enable on-demand production for pandemic response. Current methods for synthesizing favipiravir are constrained by long reaction times and low yields. If ongoing clinical trials for favipiravir demonstrate its effectiveness as a COVID-19 antiviral, and as a broad spectrum anti-viral for treating future viral outbreaks, this synthesis would help alleviate potential drug shortages and supply chain issues for the manufacturing and availability of this small molecule anti-viral. This U.S.-based synthesis route would be capable of scale-up for making large (kilogram) amounts of favipiravir as needed to assist with clinical trial needs and demand for patient treatment, and can also produce isotopically labeled favipiravir. We are seeking a CRADA partner to finalize method development who has interest in licensing the method and employing it for domestic production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Paclitaxel loading in cationic liposome vectors is enhanced by replacement of oleoyl with linoleoyl tails with distinct lipid shapes

Abstract Lipid carriers of hydrophobic paclitaxel (PTX) are used in clinical trials for cancer chemotherapy. Improving their loading capacity requires enhanced PTX solubilization. We compared the time-dependence of PTX membrane solubility as a function of PTX content in cationic liposomes (CLs) with lipid tails containing one (oleoyl; DOPC/DOTAP) or two (linoleoyl; DLinPC/newly synthesized DLinTAP) cis double bonds by using microscopy to generate kinetic phase diagrams. The DLin lipids displayed significantly increased PTX membrane solubility over DO lipids. Remarkably, 8 mol% PTX in DLinTAP/DLinPC CLs remained soluble for approximately as long as 3 mol% PTX (the solubility limit, which has been the focus of most previous studies and clinical trials) in DOTAP/DOPC CLs. The increase in solubility is likely caused by enhanced molecular affinity between lipid tails and PTX, rather than by the transition in membrane structure from bilayers to inverse cylindrical micelles observed with small-angle X-ray scattering. Importantly, the efficacy of PTX-loaded CLs against prostate cancer cells (their IC50 of PTX cytotoxicity) was unaffected by changing the lipid tails, and toxicity of the CL carrier was negligible. Moreover, efficacy was approximately doubled against melanoma cells for PTX-loaded DLinTAP/DLinPC over DOTAP/DOPC CLs. Our findings demonstrate the potential of chemical modifications of the lipid tails to increase the PTX membrane loading while maintaining (and in some cases even increasing) the efficacy of CLs. The increased PTX solubility will aid the development of liposomal PTX carriers that require significantly less lipid to deliver a given amount of PTX, reducing side effects and costs.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Evaluation of partial volume correction and analysis of longitudinal [ 18 F]GTP1 tau PET imaging in Alzheimer's disease using linear mixed-effects models

Purpose: We evaluated the impact of partial volume correction (PVC) methods on the quantification of longitudinal [ 18 F]GTP1 tau positron-emission tomography (PET) in Alzheimer's disease and the suitability of describing the tau pathology burden temporal trajectories using linear mixed-effects models (LMEM). Methods: We applied van Cittert iterative deconvolution (VC), 2-compartment, and 3-compartment, and the geometric transfer matrix plus region-based voxelwise methods to data acquired in an Alzheimer's disease natural history study over 18 months at a single imaging site. We determined the optimal PVC method by comparing the standardized uptake value ratio change (%ΔSUVR) between diagnostic and tau burden–level groups and the longitudinal repeatability derived from the LMEM. The performance of LMEM analysis for calculating %ΔSUVR was evaluated in a natural history study and in a multisite clinical trial of semorinemab in prodromal to mild Alzheimer's disease by comparing results to traditional per-visit estimates. Results: The VC, 2-compartment, and 3-compartment PVC methods had similar performance, whereas region-based voxelwise overcorrected regions with a higher tau burden. The lowest within-subject variability and acceptable group separation scores were observed without PVC. The LMEM-derived %ΔSUVR values were similar to the per-visit estimates with lower variability. Conclusion: The results indicate that the tested PVC methods do not offer a clear advantage or improvement over non-PVC images for the quantification of longitudinal [ 18 F]GTP1 PET data. LMEM offers a robust framework for the longitudinal tau PET quantification with low longitudinal test–retest variability. Clinical trial registration: NCT02640092 and NCT03289143.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Coupling Kinesin Spindle Protein and Aurora B Inhibition with Apoptosis Induction Enhances Oral Cancer Cell Killing

Many proteins regulating mitosis have emerged as targets for cancer therapy, including the kinesin spindle protein (KSP) and Aurora kinase B (AurB). KSP is crucial for proper spindle pole separation during mitosis, while AurB plays roles in chromosome segregation and cytokinesis. Agents targeting KSP and AurB selectively affect dividing cells and have shown significant activity in vitro. However, these drugs, despite advancing to clinical trials, often yield unsatisfactory outcomes as monotherapy, likely due to variable responses driven by cyclin B degradation and apoptosis signal accumulation networks. Accumulated data suggest that combining emerging antimitotics with various cytostatic drugs can enhance tumor-killing effects compared to monotherapy. Here, we investigated the impact of inhibiting anti-apoptotic signals with the BH3-mimetic Navitoclax in oral cancer cells treated with the selective KSP inhibitor, Ispinesib, or AurB inhibitor, Barasertib, aiming to potentiate cell death. The combination of BH3-mimetics with both KSP and AurB inhibitors synergistically induced substantial cell death, primarily through apoptosis. A mechanistic analysis underlying this synergistic activity, undertaken by live-cell imaging, is presented. Our data underscore the importance of combining BH3-mimetics with antimitotics in clinical trials to maximize their effectiveness.

Silva, João P. N. (ORCID:0000000344554286)↗

DOE OSTI2020

Estimation of Body Fat Percentage for Clinical Pharmacokinetic Studies in Children

Obesity is a prevalent childhood condition and the degree of adiposity appears likely to be an important covariate in the pharmacokinetics (PKs) of many drugs. We undertook these studies to facilitate the evaluation and, where appropriate, quantification of the covariate effect of body fat percentage (BF%) on PK parameters in children. We examined two large databases to determine the values and variabilities of BF% in children with healthy body weights and in those with obesity, comparing the accuracy and precision of BF% estimation by both clinical methods and demographically derived techniques. Additionally, we conducted simulation studies to evaluate the utility of the several methods for application in clinical trials. BF% was correlated with body mass index (BMI), but was highly variable among both children with healthy body weights and those with obesity. Bio‐impedance and several demographically derived techniques produced mean estimates of BF% that differed from dual x‐ray absorptiometry by < 1% (accuracy) and a SD of 5% or less (precision). Simulation studies confirmed that when the differences in precision among the several methods were small compared with unexplained between‐subject variability of a PK parameter, the techniques were of similar value in assessing the contribution of BF%, if any, as a covariate for that PK parameter. The combination of sex and obesity stage explained 68% of the variance of BF% with BMI. The estimation of BF% from sex and obesity stage can routinely be applied to PK clinical trials to evaluate the contribution of BF% as a potential covariate.

Green, Thomas P.↗