How to use meropenem in pediatric patients undergoing CKRT? Integrated meropenem pharmacokinetic model for critically ill children.

Standard dosing could fail to achieve adequate systemic concentrations in ICU children or may lead to toxicity in children with acute kidney injury. The population pharmacokinetic analysis was used to simultaneously analyze all available data (plasma, prefilter, postfilter, effluent, and urine concentrations) and provide the pharmacokinetic characteristics of meropenem. The probability of target fT > MIC attainment, avoiding toxic levels, during the entire dosing interval was estimated by simulation of different intermittent and continuous infusions in the studied population. A total of 16 critically ill children treated with meropenem were included, with 7 of them undergoing continuous kidney replacement therapy (CKRT). Only 33% of children without CKRT achieved 90% of the time when the free drug concentration exceeded the minimum inhibitory concentration (%fT > MIC) for an MIC of 2 mg/L. In dose simulations, only continuous infusions (60-120 mg/kg in a 24-h infusion) reached the objective in patients <30 kg. In patients undergoing CKRT, the currently used schedule (40 mg/kg/12 h from day 2 in a short infusion of 30 min) was clearly insufficient in patients <30 kg. Keeping the dose to 40 mg/kg q8h without applying renal adjustment and extended infusions (40 mg/kg in 3- or 4-h infusion every 12 h) was sufficient to reach 90% fT > MIC (>2 mg/L) in patients >10 kg. In patients <10 kg, only continuous infusions reached the objective. In patients >30 kg, 60 mg/kg in a 24-h infusion is sufficient and avoids toxicity. This population model could help with an individualized dosing approach that needs to be adopted in critically ill pediatric patients. Critically ill patients subjected to or not to CKRT may benefit from the administration of meropenem in an extended or continuous infusion.

Mechanistic characterization of oscillatory patterns in unperturbed tumor growth dynamics: The interplay between cancer cells and components of tumor microenvironment.

Mathematical modeling of unperturbed and perturbed tumor growth dynamics (TGD) in preclinical experiments provides an opportunity to establish translational frameworks. The most commonly used unperturbed tumor growth models (i.e. linear, exponential, Gompertz and Simeoni) describe a monotonic increase and although they capture the mean trend of the data reasonably well, systematic model misspecifications can be identified. This represents an opportunity to investigate possible underlying mechanisms controlling tumor growth dynamics through a mathematical framework. The overall goal of this work is to develop a data-driven semi-mechanistic model describing non-monotonic tumor growth in untreated mice. For this purpose, longitudinal tumor volume profiles from different tumor types and cell lines were pooled together and analyzed using the population approach. After characterizing the oscillatory patterns (oscillator half-periods between 8-11 days) and confirming that they were systematically observed across the different preclinical experiments available (p<10-9), a tumor growth model was built including the interplay between resources (i.e. oxygen or nutrients), angiogenesis and cancer cells. The new structure, in addition to improving the model diagnostic compared to the previously used tumor growth models (i.e. AIC reduction of 71.48 and absence of autocorrelation in the residuals (p>0.05)), allows the evaluation of the different oncologic treatments in a mechanistic way. Drug effects can potentially, be included in relevant processes taking place during tumor growth. In brief, the new model, in addition to describing non-monotonic tumor growth and the interaction between biological factors of the tumor microenvironment, can be used to explore different drug scenarios in monotherapy or combination during preclinical drug development.

Mechanism-Based Modeling of Perioperative Variations in Hemoglobin Concentration in Patients Undergoing Laparoscopic Surgery.

BACKGROUND: Hemoglobin concentration ([Hb]) in the perioperative setting should be interpreted in the context of the variables and processes that may affect it to differentiate the dilution effects caused by changes in intravascular volume. However, it is unclear what variables and processes affect [Hb]. Here, we modeled the perioperative variations in [Hb] to identify the variables and processes that govern [Hb] and to describe their effects. METHODS: We first constructed a mechanistic framework based on the main variables and processes related to the perioperative [Hb] variations. We then prospectively studied patients undergoing laparoscopic surgery, divided into 2 consecutive cohorts for the development and validation of the model. The study protocol consisted of serial measurements of [Hb] along with recordings of hemoglobin mass loss, blood volume loss, fluid infusion, urine volume, and inflammatory biomarkers measurements, up to 96 hours postoperatively. Mathematical fitting was performed using nonlinear mixed-effects. Additionally, we performed simulations to explore the effects of blood loss and fluid therapy protocols on [Hb]. RESULTS: We studied 154 patients: 118 enrolled in the development group and 36 in the validation group. We characterized the perioperative course of [Hb] using a mass balance model that accounted for hemoglobin losses during surgery, and a 2-compartment model that estimated fluid kinetics and intravascular volume changes. During model development, we found that urinary fluid elimination represented only 24% of the total fluid elimination, and that total fluid elimination was inhibited after surgery in a time-dependent manner and influenced by age. Also, covariate evaluation showed a significant association between the type of surgery and proportion of fluid eliminated via urine. In contrast, neither the type of infused solution, blood volume loss nor inflammatory biomarkers were found to correlate with model parameters. In the validation analysis, the model demonstrated a considerable predictive capacity, with 95% of the predicted [Hb] within -4.4 and +5.5 g/L. Simulations demonstrated that hemoglobin mass loss determined most of the postoperative changes in [Hb], while intravascular volume changes due to fluid infusion, distribution, and elimination induced smaller but clinically relevant variations. Simulated patients receiving standard fluid therapy protocols exhibited a hemodilution effect that resulted in a [Hb] decrease between 7 and 15 g/L at the end of surgery, and which was responsible for the lowest [Hb] value during the perioperative period. CONCLUSIONS: Our model provides a mechanistic and quantitative understanding of the causes underlying the perioperative [Hb] variations.

Population pharmacokinetics of sublingually administered tacrolimus in infants and young children with liver transplantation.

AIMS: Pharmacokinetics of tacrolimus after sublingual administration is not characterized in paediatric liver transplant patients. Therefore, we aimed to develop a population pharmacokinetic model of sublingually administered tacrolimus in patients who cannot swallow the capsules due to their age, sedation status and/or mechanical ventilation during the first weeks post-transplantation. METHODS: Demographic, clinical and pharmacological variables, including tacrolimus whole blood concentrations obtained from therapeutic drug monitoring and data from dense-sampling pharmacokinetic profiles, were recorded in 26 paediatric patients with biliary atresia who underwent liver transplantation between 2016 and 2021. Population pharmacokinetic analysis was performed with NONMEM v7.4. RESULTS: Disposition of tacrolimus was best characterized by a 2-compartment model with clearance achieving half of the maximum elimination capacity (CLMAX  = 4.1 L/h) at 4.6 days post-transplantation (T50 ). Compared to sedated patients, nonsedated status showed an increased first-order absorption rate constant (1.1 vs. 0.1 h-1 ) and a 24% reduction in bioavailability (FNS ) at 14 days post-transplant. The model was able to explain the oral absorption pattern in nonsedated patients as the result of gut bioavailability (0.9) and hepatic extraction ratio, with the latter being responsible for first-pass effects. Estimates of interindividual variability remained moderate (25.9% for the gut bioavailability) to high (79.8% for the apparent volume of distribution of the central compartment, and 101% for T50 ). CONCLUSION: A population pharmacokinetic model of sublingually administered tacrolimus in paediatric patients was developed to characterize different absorption mechanisms. Once the model is externally validated, the effect of post-transplant time on clearance and the sedation status may be considered in routine dosing management.

Relevance of primary lesion location, tumour heterogeneity and genetic mutation demonstrated through tumour growth inhibition and overall survival modelling in metastatic colorectal cancer.

AIMS: The aims of this work were to build a semi-mechanistic tumour growth inhibition (TGI) model for metastatic colorectal cancer (mCRC) patients receiving either cetuximab + chemotherapy or chemotherapy alone and to identify early predictors of overall survival (OS). METHODS: A total of 1716 patients from 4 mCRC clinical studies were included in the analysis. The TGI model was built with 8973 tumour size measurements where the probability of drop-out was also included and modelled as a time-to-event variable using parametric survival models, as it was the case in the OS analysis. The effects of patient- and tumour-related covariates on model parameters were explored. RESULTS: Chemotherapy and cetuximab effects were included in an additive form in the TGI model. Development of resistance was found to be faster for chemotherapy (drug effect halved at wk 8) compared to cetuximab (drug effect halved at wk 12). KRAS wild-type status and presenting a right-sided primary lesion were related to a 3.5-fold increase in cetuximab drug effect and a 4.7× larger cetuximab resistance, respectively. The early appearance of a new lesion (HR = 4.14), a large tumour size at baseline (HR = 1.62) and tumour heterogeneity (HR = 1.36) were the main predictors of OS. CONCLUSIONS: Semi-mechanistic TGI and OS models have been developed in a large population of mCRC patients receiving chemotherapy in combination or not with cetuximab. Tumour-related predictors, including a machine learning derived-index of tumour heterogeneity, were linked to changes in drug effect, resistance to treatment or OS, contributing to the understanding of the variability in clinical response.

Comparison of two pharmacokinetic-pharmacodynamic models of rocuronium bromide during profound neuromuscular block: analysis of estimated and measured post-tetanic count effect.

BACKGROUND: Profound neuromuscular block (NMB) is important in surgeries where complete immobility is considered essential to improve tracheal intubation and surgical conditions. Rocuronium bromide is a commonly used NMB agent. This work describes a noninvasive approach for estimation of post-tetanic count (PTC) based on two pharmacokinetic (PK) models, the Saldien and the De Haes models. The aim was to investigate the rocuronium bromide PK-pharmacodynamic (PD) relationship in estimating the PTC effect during profound NMB. METHODS: In this prospective, non-randomised, observational study, an induction bolus of rocuronium bromide was administered followed by continuous infusion for maintenance of a PTC of 1-2. measured every 3 min. Measurements were analysed as discrete categorical data and by applying the nonlinear mixed-effect modelling approach. Performance of the selected models was evaluated through simulation model-based diagnostics, further assessing the precision of the parameter estimates and the performance of the models at the individual level. RESULTS: Data from 30 adult patients undergoing elective abdominal or neurosurgical procedures were included. Post-tetanic count response profiles during rocuronium bromide infusion were successfully characterised using the population PD analysis. The models showed a good performance for all PTC categories, albeit with a moderate over-prediction of PTC >6. CONCLUSIONS: Our findings indicate that using plasma concentrations of rocuronium bromide estimated with either of the two models, combined with a PD model, provides equal model performance when predicting PTC. These promising results may provide an important advance in guiding rocuronium bromide administration when profound NMB in routine clinical practice is desired.

Pharmacological Probes to Validate Biomarkers for Analgesic Drug Development.

There is an urgent need for analgesics with improved efficacy, especially in neuropathic and other chronic pain conditions. Unfortunately, in recent decades, many candidate analgesics have failed in clinical phase II or III trials despite promising preclinical results. Translational assessment tools to verify engagement of pharmacological targets and actions on compartments of the nociceptive system are missing in both rodents and humans. Through the Innovative Medicines Initiative of the European Union and EFPIA, a consortium of researchers from academia and the pharmaceutical industry was established to identify and validate a set of functional biomarkers to assess drug-induced effects on nociceptive processing at peripheral, spinal and supraspinal levels using electrophysiological and functional neuroimaging techniques. Here, we report the results of a systematic literature search for pharmacological probes that allow for validation of these biomarkers. Of 26 candidate substances, only 7 met the inclusion criteria: evidence for nociceptive system modulation, tolerability, availability in oral form for human use and absence of active metabolites. Based on pharmacokinetic characteristics, three were selected for a set of crossover studies in rodents and healthy humans. All currently available probes act on more than one compartment of the nociceptive system. Once validated, biomarkers of nociceptive signal processing, combined with a pharmacometric modelling, will enable a more rational approach to selecting dose ranges and verifying target engagement. Combined with advances in classification of chronic pain conditions, these biomarkers are expected to accelerate analgesic drug development.

Modulation of intratumoural myeloid cells, the hallmark of the anti-tumour efficacy induced by a triple combination: tumour-associated peptide, TLR-3 ligand and α-PD-1.

BACKGROUND: Anti-programmed cell death 1 (PD-1)/programmed death-ligand 1 (PD-L1) monoclonal antibodies (mAbs) show remarkable clinical anti-tumour efficacy. However, rational combinations are needed to extend the clinical benefit to primary resistant tumours. The design of such combinations requires the identification of the kinetics of critical immune cell populations in the tumour microenvironment. METHODS: In this study, we compared the kinetics of immune cells in the tumour microenvironment upon treatment with immunotherapy combinations with different anti-tumour efficacies in the non-inflamed tumour model TC-1/A9. Tumour-bearing C57BL/6J mice were treated with all possible combinations of a human papillomavirus (HPV) E7 long peptide, polyinosinic-polycytidylic acid (PIC) and anti-PD-1 mAb. Tumour growth and kinetics of the relevant immune cell populations were assessed over time. The involvement of key immune cells was confirmed by depletion with mAbs and immunophenotyping with multiparametric flow cytometry. RESULTS: The maximum anti-tumour efficacy was achieved after intratumoural administration of HPV E7 long peptide and PIC combined with the systemic administration of anti-PD-1 mAb. The intratumoural immune cell kinetics of this combination was characterised by a biphasic immune response. An initial upsurge of proinflammatory myeloid cells led to a further rise in effector CD8+ T lymphocytes at day 8. Depletion of either myeloid cells or CD8+ T lymphocytes diminished the anti-tumour efficacy of the combination. CONCLUSIONS: The anti-tumour efficacy of a successful immunotherapy combination in a non-inflamed tumour model relies on an early inflammatory process that remodels the myeloid cell compartment.

Untangling Absorption Mechanisms and Variability in Bioequivalence Studies Using Population Analysis.

PURPOSE: Both inter-individual (IIV) and inter-occasion (IOV) variabilities are observed in bioequivalence studies. High IOV may be a cause of problems on the demonstration of bioequivalence, despite strict measures are taken to control it. The objective of this study is to investigate further means of controlling IIV by optimizing study design of crossover studies. METHODS: Data from 18 bioequivalence studies were used to develop population pharmacokinetics (popPK) models to characterize the absorption and disposition processes of 14 drugs, to estimate IOV for each drug substance and to evaluate possible correlations with biopharmaceutical properties of drug substances, classified in accordance to the Biopharmaceutics Drug Disposition Classification System (BDDCS). RESULTS: Plasma-pharmacokinetics profiles for the 14 drugs analyzed were successfully described using popPK. The pharmacokinetic parameters that showed greater variability were first-order rate constant of absorption, duration of the zero-order absorption process, relative bioavailability and time of latency. ISCV% estimated for Cmax seems to correlate with the log-Dose-Number for Class 1, 2 and 3, despite no direct correlation was observed between popPK model residual variability (RUV) and ISCV%. Nevertheless, higher RUV estimates were observed for Class 2 drugs in comparison to Class 1 and 3. CONCLUSION: Pharmacokinetic parameters related to drug absorption showed greater variability. Ingestion of the IMP along with 240 mL of water showed to standardize gastric emptying. Given the dependency between Cmax variability and dose-solubility ratio, for classes 2 and 4, ad libitum water intake may increase Cmax and AUC ISCV%. A water ingestion standardization until the expected Tmax of the drug is suggested.

Dual activity of PD-L1 targeted Doxorubicin immunoliposomes promoted an enhanced efficacy of the antitumor immune response in melanoma murine model.

BACKGROUND: The immunomodulation of the antitumor response driven by immunocheckpoint inhibitors (ICIs) such as PD-L1 (Programmed Death Ligand-1) monoclonal antibody (α-PD-L1) have shown relevant clinical outcomes in a subset of patients. This fact has led to the search for rational combinations with other therapeutic agents such as Doxorubicin (Dox), which cytotoxicity involves an immune activation that may enhance ICI response. Therefore, this study aims to evaluate the combination of chemotherapy and ICI by developing Dox Immunoliposomes functionalized with monovalent-variable fragments (Fab') of α-PD-L1. RESULTS: Immunoliposomes were assayed in vitro and in vivo in a B16 OVA melanoma murine cell line over-expressing PD-L1. Here, immune system activation in tumor, spleen and lymph nodes, together with the antitumor efficacy were evaluated. Results showed that immunoliposomes bound specifically to PD-L1+ cells, yielding higher cell interaction and Dox internalization, and decreasing up to 30-fold the IC50, compared to conventional liposomes. This mechanism supported a higher in vivo response. Indeed, immunoliposomes promoted full tumor regression in 20% of mice and increased in 1 month the survival rate. This formulation was the only treatment able to induce significant (p < 0.01) increase of activated tumor specific cytotoxic T lymphocytes at the tumor site. CONCLUSION: PD-L1 targeted liposomes encapsulating Dox have proved to be a rational combination able to enhance the modulation of the immune system by blocking PD-L1 and selectively internalizing Dox, thus successfully providing a dual activity offered by both, chemo and immune therapeutic strategies.

A Quantitative Systems Pharmacology Model for the Key Interleukins Involved in Crohn's Disease.

Crohn's disease (CD) is a complex inflammatory bowel disease whose pathogenesis appears to involve several immunologic defects causing functional impairment of the gut. Its complexity and the reported loss of effectiveness over time of standard of care together with the increase in its worldwide incidence require the application of techniques aiming to find new therapeutic strategies. Currently, systems pharmacology modeling has been gaining importance as it integrates the available knowledge of the system into a single computational model. In this work, the following workflow for robust application of systems pharmacology modeling was followed: 1) scope definition; 2) species selection and circulating plasma levels based on a search in the literature; 3) representation of model topology and parametrization of the interactions, after literature data extraction and curation, and the implementation of ordinary differential equations in SimBiology (MATLAB version R2018b); and 4) model curation and evaluation by visual comparison of simulated interleukin (IL) concentrations with the reported levels in plasma, and sensitivity analysis performed to confirm model robustness and identify the most influential parameters. Finally, 5) exposure to two dose levels of recombinant human IL10 was evaluated by simulation and comparison with reported clinical study results. In summary, we present a quantitative systems pharmacology model for the main ILs involved in CD developed using a standardized methodology and supported by a comprehensive repository summarizing the most relevant literature in the field. However, it has to be taken into account that external validation is still pending as available clinical data were primarily used for model training. SIGNIFICANCE STATEMENT: Crohn's disease (CD) is a complex heterogeneous inflammatory bowel disorder. Systems pharmacology modeling offers a great opportunity for integration of the available knowledge on the disease using a computational framework. As a result of this work, a comprehensive repository along with a quantitative systems pharmacology model for the main interleukins involved in CD is provided. This model is useful for the in silico evaluation of biomarkers and potential therapeutic targets and can be adapted to address research gaps regarding CD.

Semi-Mechanistic Pharmacokinetic Modeling of Lipid Core Nanocapsules: Understanding Quetiapine Plasma and Brain Disposition in a Neurodevelopmental Animal Model of Schizophrenia.

This study investigated plasma and brain disposition of quetiapine lipid core nanocapsules (QLNC) in naive and schizophrenic (SCZ-like) rats and developed a semimechanistic model to describe changes in both compartments following administration of the drug in solution (FQ) or nanoencapsulated. QLNC (1 mg/ml) presented 166 ± 39 nm, low polydispersity, and high encapsulation (93.0% ± 1.4%). A model was built using experimental data from total and unbound plasma and unbound brain concentrations obtained by microdialysis after administration of single intravenous bolus dose of FQ or QLNC to naive and SCZ-like rats. A two-compartment model was identifiable both in blood and in brain with a bidirectional drug transport across the blood-brain barrier (CLin and CLout). SCZ-like rats' significant decrease in brain exposure with FQ (decrease in CLin) was reverted by QLNC, showing that nanocarriers govern quetiapine tissue distribution. Model simulations allowed exploring the potential of LNC for brain delivery. SIGNIFICANCE STATEMENT: A population approach was used to simultaneously model total and unbound plasma and unbound brain quetiapine concentrations allowing for quantification of the rate and extent of the drug's brain distribution following administration of both free drug in solution or as nanoformulation to naive and SCZ-like rats. The model-based approach is useful to better understand the possibilities and limitations of this nanoformulation for drug delivering to the brain, opening the opportunity to use this approach to improve SCZ-treatment-limited response rates.

Modelling of neutrophil dynamics in children receiving busulfan or treosulfan for haematopoietic stem cell transplant conditioning.

AIMS: Busulfan and treosulfan are cytotoxic agents used in the conditioning regime prior to paediatric haematopoietic stem cell transplantation (HSCT). These agents cause suppression of myeloid cells leaving patients severely immunocompromised in the early post-HSCT period. The main objectives were: (i) to establish a mechanistic pharmacokinetic-pharmacodynamic (PKPD) model for the treatment and engraftment effects on neutrophil counts comparing busulfan and treosulfan-based conditioning, and (ii) to explore current dosing schedules with respect to time to HSCT. METHODS: Data on 126 patients, 72 receiving busulfan (7 months-18 years, 5.1-47.0 kg) and 54 treosulfan (4 months-17 years, 3.8-35.8 kg), were collected. In total, 8935 neutrophil count observations were recorded during the study period in addition to drug concentrations to develop a mechanistic PKPD model. Absolute neutrophil count profiles were modelled semimechanistically, accounting for transplant effects and differing set points pre- and post-transplant. RESULTS: PK were best described by 2-compartment models for both drugs. The Friberg semimechanistic neutropenia model was applied with a linear model for busulfan and a maximum efficacy model for treosulfan describing drug effects at various stages of neutrophil maturation. System parameters were consistent across both drugs. The HSCT was represented by an amount of progenitor cells enhancing the neutrophils' proliferation and maturation compartments. Alemtuzumab was found to enhance the proliferative rate under which the absolute neutrophil count begin to grow after HSCT. CONCLUSION: A semimechanistic PKPD model linking exposure to either busulfan or treosulfan to the neutrophil reconstitution dynamics was successfully built. Alemtuzumab coadministration enhanced the neutrophil proliferative rate after HSCT. Treosulfan administration was suggested to be delayed with respect to time to HSCT, leaving less time between the end of the administration and stem cell infusion.

Computational disease model of phenobarbital-induced acute attacks in an acute intermittent porphyria mouse model.

INTRODUCTION: Acute intermittent porphyria (AIP) is characterized by hepatic over-production of the heme precursors when aminolevulinic acid (ALA)-synthase 1 is induced by endogenous or environmental factors. The aim of this study was to develop a semi-mechanistic computational model to characterize urine accumulation of heme precursors during acute attacks based on experimental pharmacodynamics data and support the development of new therapeutic strategies. METHODS: Male AIP mice received recurrent phenobarbital challenge starting on days 1, 9, 16 and 30. 24-h urine excretion of ALA, porphobilinogen (PBG) and porphyrins from challenges D1, D9 and D30 constituted the training data set to build the mechanistic model using the population approach. In a second study, porphyrin and porphyrin precursor excretion from challenge D16 were used as a validation data set. RESULTS: The computational model presented the following features: (i) urinary excretion of ALA, PBG and porphyrins was governed by unmeasured circulating heme precursor amounts, (ii) the circulating amounts of ALA and PBG were the precursors of circulating amounts of PBG and porphyrins, respectively, and (iii) the phenobarbital effect linearly increased the synthesis of circulating ALA and PBG levels. The model displayed good parameter precision (coefficient of variation below 32% in all parameters), and adequately described the experimental data. Finally, a theoretical hemin effect was implemented to illustrate the applicability of the model to dosage optimization in drug therapies. CONCLUSIONS: A semi-mechanistic disease model was successfully developed to describe the temporal evolution of urinary heme precursor excretion during recurrent biochemical-induced acute attacks in AIP mice. This model represents the first computational approach to explore and optimize current and new therapies.

Optimal dynamic control approach in a multi-objective therapeutic scenario: Application to drug delivery in the treatment of prostate cancer.

Numerous problems encountered in computational biology can be formulated as optimization problems. In this context, optimization of drug release characteristics or dosing schedules for anticancer agents has become a prominent area not only for the development of new drugs, but also for established drugs. However, in complex systems, optimization of drug exposure is not a trivial task and cannot be efficiently addressed through trial-error simulation exercises. Finding a solution to those problems is a challenging task which requires more advanced strategies like optimal control theory. In this work, we perform an optimal control analysis on a previously developed computational model for the testosterone effects of triptorelin in prostate cancer patients with the goal of finding optimal drug-release characteristics. We demonstrate how numerical control optimization of non-linear models can be used to find better therapeutic approaches in order to improve the final outcome of the patients.

Colo-Pro: a pilot randomised controlled trial to compare standard bolus-dosed cefuroxime prophylaxis to bolus-continuous infusion-dosed cefuroxime prophylaxis for the prevention of infections after colorectal surgery.

Standard bolus-dosed antibiotic prophylaxis may not inhibit growth of antibiotic resistant colonic bacteria, a cause of SSIs after colorectal surgery. An alternative strategy is continuous administration of antibiotic throughout surgery, maintaining concentrations of antibiotics that inhibit growth of resistant bacteria. This study is a pilot comparing bolus-continuous infusion with bolus-dosed cefuroxime prophylaxis in colorectal surgery. This is a pilot randomised controlled trial in which participants received cefuroxime bolus-infusion (intervention arm) targeting free serum cefuroxime concentrations of 64 mg/L, or 1.5 g cefuroxime as a bolus dose four-hourly (standard arm). Patients in both arms received metronidazole (500 mg intravenously). Eligible participants were adults undergoing colorectal surgery expected to last for over 2 h. Results were analysed on an intention-to-treat basis. The study was successfully piloted, with 46% (90/196) of eligible patients recruited and 89% (80/90) of participants completing all components of the protocol. A trialled bolus-continuous dosing regimen was successful in maintaining free serum cefuroxime concentrations of 64 mg/L. No serious adverse reactions were identified. Rates of SSIs (superficial and deep SSIs) were lower in the intervention arm than the standard treatment arm (24% (10/42) vs. 30% (13/43)), as were infection within 30 days of operation (41% (17/43) vs 51% (22/43)) and urinary tract infections (2% (1/42) vs. 9% (4/43)). These infection rates can be used to power future clinical trials. This study demonstrates the feasibility of cefuroxime bolus-continuous infusion of antibiotic prophylaxis trials, and provides safety data for infusions targeting free serum cefuroxime concentrations of 64 mg/L. Trial registration: NCT02445859 .

A new immune-nanoplatform for promoting adaptive antitumor immune response.

Immunoliposomes (ILs), obtained with monoclonal antibodies (mAbs) decorating the liposome surface, are used for cancer treatment. These mAbs provide the recognition of molecules upregulated in cancer cells, like Programmed Death-Ligand 1 (PD-L1), an immune-checkpoint involved in tumor resistance, forming a complex that blocks this molecule and thereby, induces antitumor immune response. This mechanism introduces a new concept for ILs. ILs coupled to anti-PD-L1 or its Fab' fragment have been developed and in vitro/in vivo characterized. Factors such as coupling methods, PEG density and ligand size were optimized. In vitro data showed that Fab'-ILs displayed the highest PD-L1 cell interaction, correlating with a higher in vivo tumor accumulation and an increase of effector cytotoxic CD8+ T cells, providing tumor shrinkage and total regression in 20% of mice. Therefore, a novel immune-nanoplatform able to modulate the immune system has been developed, allowing the encapsulation of several agents for combinatorial therapies.

Recovery time after oral and maxillofacial ambulatory surgery with dexmedetomidine: an observational study.

OBJECTIVES: To evaluate the relationship between pharmacokinetic descriptors of dexmedetomidine (predicted area under the curve during the procedure, predicted plasma level at the end of the procedure, and duration of procedure) and sedation depth (proportion of time with bispectral index < 85 during the procedure) with recovery time after ambulatory procedures. MATERIALS AND METHODS: Clinical observational study of patients undergoing oral and maxillofacial ambulatory surgery with dexmedetomidine as sole sedative agent. Patients received a loading dose of dexmedetomidine (0.25-1 µg kg-1) followed by a maintenance infusion (0.2-1.4 µg kg-1 h-1) to keep a bispectral index < 85 until 5 min before the end of the procedure, and were transferred to a post-anesthesia care unit until criteria for discharge were met. RESULTS: Data from 75 patients was analyzed. Sedation depth was directly associated with recovery time (Pearson correlation coefficient [r] = 0.26; p = 0.024). Around 7% of the variation in recovery time was explained by the proportion of time with bispectral index < 85. No association with procedure duration (r = 0.01; p = 0.9), predicted area under the curve (r = 0.1; p = 0.4), or predicted plasma level of dexmedetomidine at the end of the procedure (r = 0.12; p = 0.3) with recovery time was observed. CONCLUSIONS: Sedation depth with dexmedetomidine could play a role in increasing recovery time after oral and maxillofacial ambulatory surgery. In our study, the pharmacokinetic descriptors of dexmedetomidine did not seem to influence recovery time. CLINICAL RELEVANCE: Sedation depth with dexmedetomidine could play a role in increasing recovery time after ambulatory procedures.

Systematic Modeling and Design Evaluation of Unperturbed Tumor Dynamics in Xenografts.

Xenograft mice are largely used to evaluate the efficacy of oncological drugs during preclinical phases of drug discovery and development. Mathematical models provide a useful tool to quantitatively characterize tumor growth dynamics and also optimize upcoming experiments. To the best of our knowledge, this is the first report where unperturbed growth of a large set of tumor cell lines (n = 28) has been systematically analyzed using a previously proposed model of nonlinear mixed effects (NLME). Exponential growth was identified as the governing mechanism in the majority of the cell lines, with constant rate values ranging from 0.0204 to 0.203 day-1 No common patterns could be observed across tumor types, highlighting the importance of combining information from different cell lines when evaluating drug activity. Overall, typical model parameters were precisely estimated using designs in which tumor size measurements were taken every 2 days. Moreover, reducing the number of measurements to twice per week, or even once per week for cell lines with low growth rates, showed little impact on parameter precision. However, a sample size of at least 50 mice is needed to accurately characterize parameter variability (i.e., relative S.E. values below 50%). This work illustrates the feasibility of systematically applying NLME models to characterize tumor growth in drug discovery and development, and constitutes a valuable source of data to optimize experimental designs by providing an a priori sampling window and minimizing the number of samples required.

Advanced Boolean modeling of biological networks applied to systems pharmacology.

Motivation: Literature on complex diseases is abundant but not always quantitative. Many molecular pathways are qualitatively well described but this information cannot be used in traditional quantitative mathematical models employed in drug development. Tools for analysis of discrete networks are useful to capture the available information in the literature but have not been efficiently integrated by the pharmaceutical industry. We propose an expansion of the usual analysis of discrete networks that facilitates the identification/validation of therapeutic targets. Results: In this article, we propose a methodology to perform Boolean modeling of Systems Biology/Pharmacology networks by using SPIDDOR (Systems Pharmacology for effIcient Drug Development On R) R package. The resulting models can be used to analyze the dynamics of signaling networks associated to diseases to predict the pathogenesis mechanisms and identify potential therapeutic targets. Availability and Implementation: The source code is available at https://github.com/SPIDDOR/SPIDDOR . Contact: itzirurzun@alumni.unav.es , itroconiz@unav.es. Supplementary information: Supplementary data are available at Bioinformatics online.