Forward and reverse translational approaches to predict efficacy of neutralizing respiratory syncytial virus (RSV) antibody prophylaxis.

BACKGROUND: Neutralizing mAbs can prevent communicable viral diseases. MK-1654 is a respiratory syncytial virus (RSV) F glycoprotein neutralizing monoclonal antibody (mAb) under development to prevent RSV infection in infants. Development and validation of methods to predict efficacious doses of neutralizing antibodies across patient populations exposed to a time-varying force of infection (i.e., seasonal variation) are necessary. METHODS: Five decades of clinical trial literature were leveraged to build a model-based meta-analysis (MBMA) describing the relationship between RSV serum neutralizing activity (SNA) and clinical endpoints. The MBMA was validated by backward translation to animal challenge experiments and forward translation to predict results of a recent RSV mAb trial. MBMA predictions were evaluated against a human trial of 70 participants who received either placebo or one of four dose-levels of MK-1654 and were challenged with RSV [NCT04086472]. The MBMA was used to perform clinical trial simulations and predict efficacy of MK-1654 in the infant target population. FINDINGS: The MBMA established a quantitative relationship between RSV SNA and clinical endpoints. This relationship was quantitatively consistent with animal model challenge experiments and results of a recently published clinical trial. Additionally, SNA elicited by increasing doses of MK-1654 in humans reduced RSV symptomatic infection rates with a quantitative relationship that approximated the MBMA. The MBMA indicated a high probability that a single dose of ≥ 75 mg of MK-1654 will result in prophylactic efficacy (> 75% for 5 months) in infants. INTERPRETATION: An MBMA approach can predict efficacy of neutralizing antibodies against RSV and potentially other respiratory pathogens.

V2 ACHER: Visualization of complex trial data in pharmacometric analyses with covariates.

Pharmacometric models can enhance clinical decision making, with covariates exposing potential contributions to variability of subpopulation characteristics, for example, demographics or disease status. Intuitive visualization of models with multiple covariates is needed because sparsity of data in visualizations trellised by covariate values can raise concerns about the credibility of the underlying model. V2 ACHER, introduced here, is a stepwise transformation of data that can be applied to a variety of static (non-ordinary-differential-equation-based) pharmacometric analyses. This work uses four examples of increasing complexity to show how the transformation elucidates the relationship between observations and model results and how it can also be used in visual predictive checks to confirm the quality of a model. V2 ACHER facilitates consistent, intuitive, single-plot visualization of a multicovariate model with a complex data set, thereby enabling easier model communication for modelers and for cross-functional development teams and facilitating confident use in support of decisions.

Impact of Low Birth Weight and Prematurity on Neonatal Raltegravir Pharmacokinetics: Impaact P1097.

BACKGROUND: HIV treatment of neonates requires identifying appropriate antiretroviral dosing regimens. Our aims were to characterize raltegravir elimination kinetics in low birth weight (LBW) neonates after maternal dosing and to develop a pharmacokinetic model to predict raltegravir plasma concentrations for term and preterm neonates. METHODS: Mothers living with HIV who received raltegravir during pregnancy and their LBW neonates participated in IMPAACT P1097 study. Up to 6 serial plasma samples were collected from each infant over the first 2 postnatal weeks to characterize raltegravir elimination. Safety laboratory evaluations were obtained, and infants were monitored for 6 weeks for signs of raltegravir toxicity. An integrated maternal-neonatal pharmacokinetic model was developed to predict neonatal raltegravir plasma concentrations. RESULTS: Sixteen mothers and their 18 LBW neonates were enrolled. The median (range) raltegravir elimination half-life was 24.4 (10.1-83) hours (N = 17 neonates). No adverse events related to raltegravir in utero exposure were observed. Pharmacokinetic modeling revealed that raltegravir clearance in full-term LBW neonates was well described by allometric scaling but clearance in preterm LBW neonates was better described using slower clearance maturation kinetics. Simulations suggest receipt of the current dosing recommendations in a 34-week gestation neonate would result in plasma concentrations up to 2.5-fold higher than those observed in full-term LBW infants. CONCLUSIONS: Modeling suggests that prematurity reduces raltegravir clearance and a modified raltegravir dosing regimen will be necessary to avoid elevated plasma raltegravir concentrations.

Raltegravir (RAL) in Neonates: Dosing, Pharmacokinetics (PK), and Safety in HIV-1-Exposed Neonates at Risk of Infection (IMPAACT P1110).

BACKGROUND: Adequate pharmacokinetic and safety data in neonates are lacking for most antiretroviral agents. Raltegravir is a selective HIV-1 integrase strand transfer inhibitor available in a granule formulation suitable for use in neonates and young infants as prophylaxis or treatment of HIV infection. METHODS: IMPAACT P1110 is a phase 1, multicenter, noncomparative dose-finding study of raltegravir in infants exposed to HIV-1 infection. A 2-cohort adaptive design was utilized where pharmacokinetic data from infants in cohort 1 who received 2 single doses of raltegravir 3 mg/kg were included in population modeling and simulations to guide selection of a daily dose for infants in cohort 2. RESULTS: A total of 52 infants enrolled in IMPAACT 1110: cohort 1 (N = 16) and cohort 2 (N = 36). Using simulations based on population PK modeling incorporating cohort 1 data, the following daily dosing regimen was selected for study: 1.5 mg/kg daily from birth through day 7; 3 mg/kg twice daily from days 8-28 of life; and 6 mg/kg twice daily after 4 weeks of age through 6 weeks of age. The geometric mean protocol exposure targets for AUC, Ctrough, and Cmax were met or slightly exceeded in all infants. The chosen neonatal raltegravir dosing regimen was safe and well tolerated in full-term neonates during treatment over the first 6 weeks of life and follow-up to age 24 weeks. CONCLUSIONS: Raltegravir can be safely administered to full-term infants using the daily dosing regimen studied. This regimen is not recommended for use in premature infants in a new version of P1110.

Use of Modeling and Simulations to Determine Raltegravir Dosing in Neonates: A Model for Safely and Efficiently Determining Appropriate Neonatal Dosing Regimens: IMPAACT P1110.

BACKGROUND: Population modeling and simulations can be used to facilitate the conduct of phase I studies to develop safe and effective dosing regimens in neonates. SETTING: P1110 is an international, multicenter trial to determine safe and effective raltegravir doses in neonates at risk for HIV infection. METHODS: P1110 used a 2-cohort adaptive design incorporating population pharmacokinetic modeling and simulations. An initial cohort of neonates received 2 single oral doses of raltegravir with standard-of-care therapy for prevention of perinatal transmission-one within 48 hours of birth and a second at 7-10 days of life. Raltegravir concentration data after administration of these doses were combined with data from a previous study of infants aged 4 weeks to 2 years. The combined database was used for population pharmacokinetic modeling and simulations to select a daily dosing regimen for investigation in a second cohort of neonates. RESULTS: Raltegravir concentration data from 6 neonates were combined with data from infants aged 4 weeks to 2 years receiving raltegravir twice daily. The combined data set allowed for successful development of a population pharmacokinetic model with reasonable precision of parameter estimates. Monte Carlo simulations were run to evaluate potential daily dosing regimens from birth to 6 weeks of age, allowing for selection of a regimen to be evaluated in a subsequent cohort of neonates receiving chronic raltegravir dosing. CONCLUSIONS: An adaptive design incorporating population pharmacokinetic modeling and simulations was used to select a developmentally appropriate neonatal raltegravir dosing regimen in the first 6 weeks of life.

Maternal-Neonatal Raltegravir Population Pharmacokinetics Modeling: Implications for Initial Neonatal Dosing.

Raltegravir readily crosses the placenta to the fetus with maternal use during pregnancy. After birth, neonatal raltegravir elimination is highly variable and often extremely prolonged, with some neonates demonstrating rising profiles after birth despite removal from the source of extrinsic raltegravir. To establish an appropriate dosing regimen, an integrated maternal-neonatal pharmacokinetics model was built to predict raltegravir plasma concentrations in neonates with in utero raltegravir exposure. Postnatal age and body weight were used as structural covariates. The model predicted rising or decreasing neonatal elimination profiles based on the time of maternal drug administration relative to time of birth and degree of in utero drug disposition into the central and peripheral compartments. Based on this model, it is recommended to delay the first oral dose of raltegravir until 1-2 days of age in those neonates born to mothers who received raltegravir during pregnancy, labor, and delivery.

Novel ATP competitive MK2 inhibitors with potent biochemical and cell-based activity throughout the series.

Optimization of our previously described pyrrolopiperidone series led to the identification of a new benzamide sub-series, which exhibits consistently high potency in biochemical and cell-based assays throughout the series. Strong inhibition of LPS-induced production of the cytokine TNFα is coupled to the regulation of HSP27 phosphorylation, indicating that the observed cellular effects result from the inhibition of MK2. X-ray crystallographic and computational analyses provide a rationale for the high potency of the series.

A new highly androgen specific yeast biosensor, enabling optimisation of (Q)SAR model approaches.

Recently we constructed recombinant yeast cells that express the human androgen receptor (hAR) and yeast enhanced green fluorescent protein (yEGFP), the latter in response to androgens. When exposed to 17beta-testosterone, the concentration where half-maximal activation is reached (EC50) was 50 nM. Relative androgenic potencies (RAP), defined as the ratio between the EC50 of 17beta-testosterone and the EC50 of the compound, were 1.7, 1.2 and 0.008 for 19-nortestosterone, tetrahydrogestrinone and 17beta-estradiol respectively. Steroids representative for other hormone receptors, like estrone, 17alpha-ethynylestradiol, and diethylstilbestrol for the estrogen receptor and corticosterone and dexamethasone for the glucocorticoid receptor, showed no agonistic response. Only compounds known to exert androgenic effects give a response. Determined RAPs were in line with results obtained from optimised QSAR model calculations and demonstrated that Saccharomyces cerevisiae showed no metabolism of test compounds and displayed no crosstalk from endogenous hormone receptors. The suitability of this bioassay to verify the outcomes of (Q)SAR models to predict the activities of different steroids was further examined by studies with steroid isomers and a number of designer steroids, confirming that the 17beta-hydroxyl group, 3-keto group and 5alpha-steroidal framework are extremely important for the activity of the androgenic steroid.

Some molecular descriptors for non-specific chromosomal genotoxicity based on hydrophobic interactions.

A concept relating the lipophilicity of chemicals with their genotoxicity on a chromosomal level had been generated by Schultz and Onfelt (Chem Biol Interact 126:97-123, 2000). It was shown that aneuploidy in Chinese hamster V79 cells was elicited by lipophilic chemicals at concentrations related to their hydrophobicity (log P), whereas toxicants with a specific mode of action acted at concentrations consistently lower than predicted based on log P. We have now combined available data sets on aneuploidy/micronucleus formation with procedures used in QSAR modelling, in order to find new molecular descriptors for modelling non-specific chromosomal genotoxicity, and to optimise combinations thereof. Molecular structures of 26 chemicals, including steroids, were converted into single 3D models using Corina (version 3.20), and 11 descriptors of molecular properties were calculated. The data of 16 compounds assigned to a non-specific mode of action were imported into the QSAR module of the software package Cerius(2) (version 4.10). Applying genetic function approximation (GFA), linear equations were set up relating molecular descriptors with experimental concentrations at which doubling of micronuclei occurred in V79 cells (exp -log C). The number of variables (molecular descriptors) was limited to a maximum of three, and linear and quadratic terms were allowed. Based on the descriptions provided by the GFA procedure, log P was the most suitable single property to describe non-specific genotoxicity [r (2 ) = 0.88], confirming the original concept of Schultz and Onfelt. Using more descriptors (up to three in combination) resulted in an optimization of correlations up to r (2 )= 0.97. Such optimal correlation coefficients were obtained by combinations (a) of the numbers of hydrogen bond acceptors, the polar surface and total surface areas of molecules on one hand, and by (b) the dipole moment, polar surface and total surface descriptors on the other hand. In essence, the relation of polar surface to the total molecular surface appears pivotal to determine the non-specific chromosomal genotoxicity of lipophilic compounds.

The quest for bioisosteric replacements.

To help advance drug discovery projects, a new and validated search method is presented by which potential bioisosteric replacements can be retrieved from a database of more than 700,000 structural fragments. The heart of the search method is an optimized topological pharmacophore fingerprint which describes each fragment as a combination of attachment points, hydrogen bond donors and acceptors, hydrophobic centers, conjugated atoms, and non-hydrogen atoms. In the fingerprint the influence of the attachment point is enhanced by giving it extra weight relative to the other descriptors. The Euclidean distance has proven to be the optimum distance measure to compare the fingerprints in a database search. The performance of the pharmacophore fingerprint based search method has been validated using more than 2200 bioisosteric fragment pairs extracted in an unbiased procedure from the BIOSTER database. The true bioisosteric pairs have been compared with pairs of random fragments originating from the WDI database. Normalized by the standard deviation of the random pairs distance distributions, an excellent separation of true pairs from random pairs was obtained for R-group fragments (2.2 standard deviation units) as well as for linkers (2.6 units) and cores (2.6 units). The bioisoster search method has been implemented as an intranet application called IBIS and is now routinely used by Organon researchers.

Conformational analysis of two xylose-containing N-glycans in aqueous solution by using 1H NMR ROESY and NOESY spectroscopy in combination with MD simulations.

The conformational behavior of the synthetic hexa- and heptasaccharide methyl beta-glycosides alpha-D-Manp-(1 --> 6)-[alpha-D-Manp-(1 --> 3)-][beta-D-Xylp-(1 --> 2)-]beta-D-Manp-(1 --> 4)-beta-D-GlcpNAc-(1 --> 4)-beta-D-GlcpNAc-(1 --> OMe and alpha-D-Manp-(1 --> 6)-[alpha-D-Manp-(1 --> 3)-][beta-D-Xylp-(1 --> 2)-]beta-D-Manp-(1 --> 4)-beta-D-GlcpNAc-(1 --> 4)-[alpha-L-Fucp-(1 --> 6)-]beta-D-GlcpNAc-(1 --> OMe, representing the xylosylated and the xylosylated alpha-(1 --> 6)-fucosylated core structures of N-glycans in alpha(D)-hemocyanin of the snail Helix pomatia, respectively, were investigated by 1H NMR spectroscopy in combination with molecular dynamics (MD) simulations in water. 1H and 13C chemical shifts of the oligosaccharides were assigned using 1H-(1)H COSY, TOCSY, and NOESY, and 1H-(13)C HMQC techniques. Experimental 2D 1H cross-peak intensities from one series of NOESY and one series of ROESY experiments of the two oligosaccharides were compared with calculated values derived from MD trajectories using the CROSREL program, yielding information about the conformation of each glycosidic linkage of the methyl glycosides. The flexibility of the linkages was described by generalized order parameters and internal rotation correlation times. Analysis of the data indicated that several conformations are likely to exist for the alpha-D-Man-(1 --> 6)-beta-D-Man, the alpha-L-Fuc-(1 --> 6)-beta-D-GlcNAc, and the alpha-D-Man-(1 --> 3)-beta-D-Man linkage, whereas the beta-D-Xyl-(1 --> 2)-beta-D-Man-(1 --> 4)-beta-D-GlcNAc-(1 --> 4)-beta-D-GlcNAc fragment occurs in one rigid conformation. No significant differences were found between the corresponding structural elements in both methyl glycosides. NOESY and ROESY experiments proved to be suitable for providing the experimental data required, however, due to more overlap within the ROESY spectra, reducing the accuracy of the analysis, NOESY spectral analysis is preferred.

Crystal structure prediction of small organic molecules: a second blind test.

The first collaborative workshop on crystal structure prediction (CSP1999) has been followed by a second workshop (CSP2001) held at the Cambridge Crystallographic Data Centre. The 17 participants were given only the chemical diagram for three organic molecules and were invited to test their prediction programs within a range of named common space groups. Several different computer programs were used, using the methodology wherein a molecular model is used to construct theoretical crystal structures in given space groups, and prediction is usually based on the minimum calculated lattice energy. A maximum of three predictions were allowed per molecule. The results showed two correct predictions for the first molecule, four for the second molecule and none for the third molecule (which had torsional flexibility). The correct structure was often present in the sorted low-energy lists from the participants but at a ranking position greater than three. The use of non-indexed powder diffraction data was investigated in a secondary test, after completion of the ab initio submissions. Although no one method can be said to be completely reliable, this workshop gives an objective measure of the success and failure of current methodologies.