Browsing by Author "Smith, Brandon"

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    211. Defining Optimal Sampling Times for Cefepime Therapeutic Drug Monitoring in Clinical Practice
    (Oxford University Press, 2025-01-29) Rhodes, Nathaniel J.; Smith, Brandon; Shields, Ryan K.; Pan, Samantha; Weslander, Erin; Galvin, Shannon; Hughes, Jasmine; Hughes, Maria-Stephanie; Sime, Fekade B.; Roberts, Jason A.; Kiel, Patrick J.; Neely, Michael N.; Scheetz, Marc H.; Medicine, School of Medicine
    Background: Clinicians performing beta-lactam therapeutic drug monitoring (TDM) lack evidence on when levels should ideally be drawn after a dose. Herein, we define the optimal timing (i.e., optimal sampling) for cefepime using real-world TDM data to validate our approach. Methods: De-identified data from two centers performing routine cefepime TDM were extracted by InsightRX and served as an external validation cohort. Plasma cefepime was quantified using validated LC-MS/MS assays for TDM and dosing was protocolized at each site. CRRT and ECMO patients were included but other dialysis patients were not. Bias (MPE) and precision (RMSE) of a non-parametric prior were assessed. Multiple-model optimal (MM-opt) sampling strategies were estimated for the first 24 hours of treatment. To mirror clinical practice, one- and two-sample designs were evaluated. Dose and covariate values informed optimal sampling times. Bayesian PK exposures were compared using all samples, trough-only sampling, or using a single optimally timed sample. AUCs were calculated from the posteriors. For fT >MIC analysis, the MIC was fixed at 8 mg/L. We used Pmetrics 2.1.1 for R. Results: 116 patients (42% female; median age, CRCL, and weight: 62 years, 76 mL/min, and 80 kg, respectively) contributed 235 levels. The PK model demonstrated acceptable bias and precision (-6% MPE, 30.9 RMSE) as a prior for estimating exposures from the TDM data (Fig1). For a one-sample approach, the most common MM-opt sampling times varied (Fig2) but were often a mid-point or trough. In the two-sample approach, sample one was often a mid-point and sample two was often a trough (Fig3). First 24-hr AUC and fT>MIC did not significantly differ using all available samples for analysis vs. limiting sampling to a single optimized time point vs. limiting sampling to a trough-only approach (P >0.05 for all comparisons; Fig4). Conclusion: Optimal cefepime sampling times depended on dosing regimen, and renal disposition. When limited to a single sample, optimal sampling times for cefepime TDM were often midpoint/trough levels, but when two samples were obtained the optimal sampling times were often a mid-point followed by a trough. Estimation of PK and PK/PD exposures was not significantly worse when using a validated Bayesian prior and a trough-only sampling approach.
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    Advancing cyanobacteria biomass estimation from hyperspectral observations: Demonstrations with HICO and PRISMA imagery
    (Elsevier, 2021-12) O'Shea, Ryan E.; Pahlevan, Nima; Smith, Brandon; Bresciani, Mariano; Egerton, Todd; Giardino, Claudia; Li, Lin; Moore, Tim; Ruiz-Verdu, Antonio; Ruberg, Steve; Simis, Stefan G. H.; Stumpf, Richard; Vaičiūtė, Diana; Earth Sciences, School of Science
    Retrieval of the phycocyanin concentration (PC), a characteristic pigment of, and proxy for, cyanobacteria biomass, from hyperspectral satellite remote sensing measurements is challenging due to uncertainties in the remote sensing reflectance (∆Rrs) resulting from atmospheric correction and instrument radiometric noise. Although several individual algorithms have been proven to capture local variations in cyanobacteria biomass in specific regions, their performance has not been assessed on hyperspectral images from satellite sensors. Our work leverages a machine-learning model, Mixture Density Networks (MDNs), trained on a large (N = 939) dataset of collocated in situ chlorophyll-a concentrations (Chla), PCs, and remote sensing reflectance (Rrs) measurements to estimate PC from all relevant spectral bands. The performance of the developed model is demonstrated via PC maps produced from select images of the Hyperspectral Imager for the Coastal Ocean (HICO) and Italian Space Agency's PRecursore IperSpettrale della Missione Applicativa (PRISMA) using a matchup dataset. As input to the MDN, we incorporate a combination of widely used band ratios (BRs) and line heights (LHs) taken from existing multispectral algorithms, that have been proven for both Chla and PC estimation, as well as novel BRs and LHs to increase the overall cyanobacteria biomass estimation accuracy and reduce the sensitivity to ∆Rrs. When trained on a random half of the dataset, the MDN achieves uncertainties of 44.3%, which is less than half of the uncertainties of all viable optimized multispectral PC algorithms. The MDN is notably better than multispectral algorithms at preventing overestimation on low (<10 mg m−3) PC. Visibly, HICO and PRISMA PC maps show the wider dynamic range that can be represented by the MDN. The available in situ and satellite-derived Rrs matchups and measured in situ PC demonstrate the robustness of the MDN for estimating low (<10 mg m−3) PC and the reduced impact of ∆Rrs on medium-to-high in situ PC (>10 mg m−3). According to our extensive assessments, the developed model is anticipated to enable practical PC products from PRISMA and HICO, therefore the model is promising for planned hyperspectral missions, such as the Plankton Aerosol and Cloud Ecosystem (PACE). This advancement will enhance the complementary roles of hyperspectral radiometry from satellite and low-altitude platforms for quantifying and monitoring cyanobacteria harmful algal blooms at both large and local spatial scales.
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    Hyperspectral retrievals of phytoplankton absorption and chlorophyll-a in inland and nearshore coastal waters
    (Elsevier, 2021-02) Pahlevan, Nima; Smith, Brandon; Binding, Caren; Gurlin, Daniela; Li, Lin; Bresciani, Mariano; Giardino, Claudia; Earth Sciences, School of Science
    Following more than two decades of research and developments made possible through various proof-of-concept hyperspectral remote sensing missions, it has been anticipated that hyperspectral imaging would enhance the accuracy of remotely sensed in-water products. This study investigates such expected improvements and demonstrates the utility of hyperspectral radiometric measurements for the retrieval of near-surface phytoplankton properties1, i.e., phytoplankton absorption spectra (aph) and biomass evaluated through examining the concentration of chlorophyll-a (Chla). Using hyperspectral data (409–800 nm at ~5 nm resolution) and a class of neural networks known as Mixture Density Networks (MDN) (Pahlevan et al., 2020), we show that the median error in aph retrievals is reduced two-to-three times (N = 722) compared to that from heritage ocean color algorithms. The median error associated with our aph retrieval across all the visible bands varies between 20 and 30%. Similarly, Chla retrievals exhibit significant improvements (i.e., more than two times; N = 1902), with respect to existing algorithms that rely on select spectral bands. Using an independent matchup dataset acquired near-concurrently with the acquisition of the Hyperspectral Imager for the Coastal Ocean (HICO) images, the models are found to perform well, but at reduced levels due to uncertainties in the atmospheric correction. The mapped spatial distribution of Chla maps and aph spectra for selected HICO swaths further solidify MDNs as promising machine-learning models that have the potential to generate highly accurate aquatic remote sensing products in inland and coastal waters. For aph retrieval to improve further, two immediate research avenues are recommended: a) the network architecture requires additional optimization to enable a simultaneous retrieval of multiple in-water parameters (e.g., aph, Chla, absorption by colored dissolved organic matter), and b) the training dataset should be extended to enhance model generalizability. This feasibility analysis using MDNs provides strong evidence that high-quality, global hyperspectral data will open new pathways toward a better understanding of biodiversity in aquatic ecosystems.
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    Pharmacokinetics and Pharmacodynamics of an Antibody Targeting Pathological Tau for the Treatment of Alzheimer’s Disease: Nonclinical Studies in P301S Mice and Cynomolgus Macaques
    (Wiley, 2025-01-09) Sadhu, Chanchal; Liu, Wencheng; Kundu, Joydip; Thompson, Jeffery; Emery, Maurice; Epling, Daniel; Smith, Brandon; Shah, Ishan; Paranjpe, Maneesha; Lee, Shiron; Fang, Ching-Lien; Walsh, Alison; Placidi, Matteo; Mathur, Krishanu; Mondick, John; Chapel, Sunny; Ghetti, Bernardino; Carter, Todd; Paul, Steven M.; Yao, Johnny; Sah, Dinah W. Y.; Pathology and Laboratory Medicine, School of Medicine
    Background: VY‐TAU01 is a recombinant humanized IgG4 monoclonal antibody (mAb) directed against pathological tau for the treatment of patients with mild dementia or mild cognitive impairment due to Alzheimer’s disease (AD). Both VY‐TAU01 and its parental mouse IgG1 mAb Ab‐01 target an epitope in the C‐terminus of tau, bind pathological tau with high affinity and selectivity over wild‐type tau, block paired helical filament seed‐induced tau aggregates in vitro, and selectively stain tau tangles in AD and P301S mouse (C57/B6J‐Tg[Thy1‐MAPT*P301S]2541Godt) brain. Ab‐01 robustly inhibits seeding and propagation of pathological tau in a P301S mouse seeding model. To support toxicology studies and the initiation of the first‐in‐human study, nonclinical studies have been conducted to characterize the pharmacokinetics (PK) and pharmacodynamics (PD) of Ab‐01 in P301S mice and the PK of VY‐TAU01 in cynomolgus macaques. Method: The PK of Ab‐01 in the P301S mouse after 5 weekly intravenous or intraperitoneal doses at 10 to 120 mg/kg and VY‐TAU01 in cynomolgus macaques after a single intravenous high or mid dose was evaluated with validated ELISAs using their target epitope peptide. The PD of Ab‐01 in the P301S mouse was also evaluated using an ELISA to quantify unbound p‐tau levels. Result: Ab‐01 and VY‐TAU01 PK profiles in serum and cerebrospinal fluid (CSF) were characterized by a distribution phase followed by a typical elimination phase without evidence of substantial target‐mediated disposition in the respective compartments. Serum and CSF concentrations increased with increasing dose levels in an approximately dose proportional manner, and their half‐lives were approximately 9 to 13 days. CSF concentrations were 0.1 ‐ 0.2% of serum concentrations. PD effects of Ab‐01 in the P301S mouse were robust, with up to ∼90% lowering of unbound p‐tau. Additional PD as well as PK/PD modeling results will also be presented. Conclusion: The PK of Ab‐01 in the P301S mouse and VY‐TAU01 in the cynomolgus macaque, and CSF to serum ratios were typical of murine IgG1 and human IgG4 administered to these respective species. The PD of Ab‐01 in the P301S mouse demonstrated robust lowering of unbound p‐tau. These results support VY‐TAU01’s continued development and advancement into the clinic.