Amphotericin B (AmB), a potent amphiphilic drug with antifungal and antileishmanial properties, exhibits reduced nephrotoxicity when delivered via lipid-based systems like microemulsions (ME). However, the complexity of these multi-phasic systems challenges the use of simple schemes and models for describing AmB degradation. The aim of this study was to establish a degradation scheme and model for AmB within a ME, alongside a control micellar formulation. AmB degradation pathways and models in both lipidic and aqueous systems were evaluated based on prior research. Experimental investigations into interface degradation pathways were conducted using a micellar approach. High-Performance Liquid Chromatography (HPLC) was employed for AmB quantification. Oxidation emerges as the principal degradation pathway within micelles, dependent on surfactant-induced aggregation. Considering AmB's behavior in distinct media (lipidic, aqueous, and micellar), an empirical degradation scheme is proposed, translated into a complex multi-pathway mathematical model capable of describing experimental data on AmB degradation in ME under dark conditions. Aggregation and oxidation played significant roles, and kinetic constants were calculated for AmB in ME. The model presented here represents a significant step toward accurately describing the non-linear degradation of AmB in prospective liquid lipid-based dispersions, potentially advancing its market prospects.

Amphotericin B (AmB) is a potent antimicrobial agent used in clinical practice. Nevertheless, the mechanism of its aqueous instability remains not yet fully understood, especially the role that its aggregation state plays in this process. Therefore, the current study used an aqueous methanol media to evaluate the AmB instability as a function of pH-, organic solvent- and concentration-dependent ionization and aggregation. To reach this goal, the aggregation status and instability were determined using UV-vis spectroscopy, LC-MS and HPLC. Moreover, not only the hydrolytic degradation products were identified by UV-vis spectroscopy and LC-MS, but also, the degradation rate constants were estimated by nonlinear regression. The results indicated that monomeric AmB was the predominant species under pH conditions, wherein the substrate was cationic (pH < 4) or anionic (pH > 9). On the other hand, aggregated AmB form was the predominant species for the zwitterionic substrate (at methanol concentration < 30 %(v/v)). Anionic substrate degraded by specific base-catalyzed lactone hydrolysis. Oxidation accounted for the loss of zwitterionic substrate. Aggregated zwitterionic AmB exhibited lower stability than monomeric zwitterionic AmB under neutral pH conditions. These studies are a step forward in comprehending the degradation kinetics of AmB in aqueous medium. In fact, along with our previous research on AmB instability in oils, it leads to a better understanding of the AmB stability in complex systems with an oil-water interface, such as disperse lipid systems.

The purpose of this work was to determine the degradation pathway of Amphotericin B (AmB) and its kinetics in lipid-based solutions. Mixtures of AmB in lipophilic solvent media were stored under different conditions, such as surface area, temperature, light exposure, presence of antioxidants and other co-solutes. AmB was quantified by HPLC and UV-Vis spectrometry. Empirical models were proposed, and degradation rate constants were estimated by nonlinear regression. The HPLC method was precise and accurate with linearity from 4.45 to 52.0 nM. Surface area studies revealed that adsorption to glass did not affect AmB loss. Unsaturated oils and methanol better preserved AmB compared to medium chain-triglyceride. Temperature increased AmB loss in a nonlinear behavior and the presence of antioxidants reduced its degradation. Under dark conditions, autoxidation was the predominant degradation pathway of AmB in oil, which undergoes a complex degradation. Under light exposure, photo-oxidation accounted for AmB loss, which appeared to be of pseudo-first order. AmB oily samples should be preferably stored in glass vials protected from light with the addition of antioxidants. Furthermore, this work encourages further investigation in other media for future complex modeling and estimation of AmB degradation and kinetics in lipid-based formulations.

Purpose The purpose of the research described herein was to develop a kinetic model for quantifying the effects of conditional and compositional variations on non-covalent polymorphic and covalent chemical transformations of gabapentin. Methods Kinetic models that describe the relationship between polymorphs and degradation product in a series of sequential or parallel steps were devised based on analysis of the resultant concentration time profiles. Model parameters were estimated using non-linear regression and Bayesian methods and evaluated in terms of their quantitative relationship to compositional and conditional variations. Results The model was constructed in which co-milling gabapentin with excipients determined three physically-initial concentrations (II 0 *, II 0 and III 0 ) and one chemically-initial concentration (lactam 0 ). For chemical transitions, no humidity effect was present but the catalytic effects of excipients on the conversion of II and III➔lactam were observed. For physical transition, excipient primarily influenced the physical state transition of III➔II through its ability to interact with humidity. Conclusions This model was shown to be robust to quantitatively account for the effects of temperature, humidity and excipient on rate constants associated with kinetics for each physical and chemical transition.

In the previous work, a reduced-order population pharmacokinetic (PK) model was used within a Bayesian inference framework to predict individualized patient dosing regimens. It was shown that a reduced-order model was adequate for individualized dosing of gabapentin given a minimum number of plasma samples from the given patient. However, this purely empirical model could not explain why patients have such different dosing needs. Accordingly, in this work, we couple an advanced compartment and transit oral absorption model with a full physiologically based PK model parameterized using a two-level hierarchical Bayesian approach. The coupled model provides the capability to not only understand the variable oral absorption but also the disposition of the drug. The proposed model-based strategy to individualized dosing is applied to the dosing of gabapentin using the retrospective data from the literature. The computations show that a standard starting regimen of 300 mg every 8 h is not likely to result in efficacious dosing for a substantial proportion of patients. Additionally, the proposed approach was able to incorporate urine data in a seamless way to inform the extent of absorption without assuming that the data were perfect. The mechanistic absorption model elucidated that the uncertainty in absorption plays a role in the variability in exposure seen across the patient population. It has also been suggested that the apparent absorption site is likely not the full upper GI, but a very localized segment due to the transit times required to fit the data. In this study, model implementation and Markov chain Monte Carlo computations were performed using the CmdStan package.

A quantitative, model-based risk assessment process was evaluated using Bayesian parameter estimation to determine the posterior distribution of the probability of a model tablet formulation’s (gabapentin) ability to meet end-of-expiry stability criteria-based manufacturing controls. Experimental data was obtained from an FDA-supported, multi-year project that involved researchers at nine universities working collaboratively with industrial and governmental scientists under the leadership of the National Institute for Pharmaceutical Technology and Education (NITPE). The risk assessment process involved the development of a design space manufacturing model and shelf life stability model that shared stability-related critical quality attributes (CQAs). Monte Carlo simulations of the design space and shelf life models that uses model parameter uncertainty to estimate the probability of shelf life failure as a function of manufacturing control. The resultant linked design space and shelf life stability models were tested by comparing model predicted and observed long-term stability data generated under a variety of pilot scale production conditions.

The use of particle size distribution (PSD) similarity metrics and the development and incorporation of drug release predictions based on PSD properties into PBPK models for various drug administration routes may provide a holistic approach for evaluating the effect of PSD differences on in vitro drug release and bioavailability of disperse systems. The objectives of this study were to provide a rational approach for evaluating the utility of in vitro PSD comparators for predicting bioequivalence for subcutaneously administered test and reference drug emulsions. Two types of in vitro comparators for test and reference emulsion products were evaluated: PSD characterization comparators (overlap metrics, median, and span ratios) and release profile comparators (f2 and various fractional time ratios). A subcutaneous-input PBPK disposition model was developed to simulate blood concentration-time profiles of reference and test emulsion products and pharmacokinetic responses (e.g., AUC, Cmax, and Tmax) were used to determine bioequivalence. A pool of 10,440 pairs of test and reference products was simulated using Monte Carlo experiments. The PSD and release profile comparators were correlated to pass/fail bioequivalence metrics using logistical regression. Based on the use of single in vitro comparators, the f2 method was the best predictor of bioequivalence prediction. The use of combinations of f2 and PSD overlap comparators (e.g., OVL or PROB) improved bioequivalence prediction to about 90%. Simulation procedures used in this study demonstrated a process for developing reliable in vitro BE predictors.

Gabapentin was used as a model pharmaceutical compound with susceptibility to polymorphic transformation as a function of environmental and mechanical stress. The utility of 13C CP/MAS NMR and XRPD as stability-indicating methods to quantify polymorphic transformation kinetics was investigated. Polymorphic Form II and III were distinguishable based on their chemical shift and distinct diffraction peak differences. Reproducible and accurate quantification of polymorphic composition in the presence of selected excipients was demonstrated using both signals from 13C CP/MAS NMR spectra and XRPD patterns. The effect of excipients on polymorphic transformations (Form II→III) was determined by measuring the transformation after co-milling. Both 13C CP/MAS NMR and XRPD were capable of measuring polymorphic composition in co-milled excipient mixtures without excipient peak interference. The amounts of Form III present in co-milled mixtures containing colloidal silicon dioxide, starch, hydroxy propyl cellulose and dibasic calcium phosphate were 8.7, 21, 33, and 39mol%, respectively. A quenching procedure for obtaining 13C CP/MAS NMR spectra and environmentally-controlled XRPD were devised to determine polymorphic transformation kinetics of co-milled excipient mixtures during storage.

Patient safety risk due to toxic degradation products is a potentially critical quality issue for a small group of useful drug substances. Although the pharmacokinetics of toxic drug degradation products may impact product safety, these data are frequently unavailable. The objective of this study is to incorporate the prediction capability of physiologically based pharmacokinetic (PBPK) models into a rational drug degradation product risk assessment procedure using a series of model drug degradants (substituted anilines). The PBPK models were parameterized using a combination of experimental and literature data and computational methods. The impact of model parameter uncertainty was incorporated into stochastic risk assessment procedure for estimating human safe exposure levels based on the novel use of a statistical metric called "PROB" for comparing probability that a human toxicity-target tissue exposure exceeds the rat exposure level at a critical no-observed-adverse-effect level. When compared with traditional risk assessment calculations, this novel PBPK approach appeared to provide a rational basis for drug instability risk assessment by focusing on target tissue exposure and leveraging physiological, biochemical, biophysical knowledge of compounds and species.

The interaction mechanism of lipopeptide antibiotic daptomycin and polyamidoamine (PAMAM) dendrimers was studied using fluorescence spectroscopy. The fluorescence changes observed are associated with daptomycin-dendrimer interactions. The binding isotherms were constructed by plotting the fluorescence difference at 460 nm from kynurenine (Kyn-13) of daptomycin in the presence and absence of dendrimer. A one-site and two-site binding model were quantitatively generated to estimate binding capacity and affinity constants from the isotherms. The shape of the binding isotherm and the dependence of the estimated capacity constants on dendrimer sizes and solvent pH values provide meaningful insight into the mechanism of interactions. A one-site binding model adequately describes the binding isotherm obtained under a variety of experimental conditions with dendrimers of various sizes in the optimal binding pH region 3.5 to 4.5. Comparing the pH-dependent binding capacity with the ionization profiles of daptomycin and dendrimer, the ionized aspartic acid residue (Asp-9) of daptomycin primarily interact with PAMAM cationic surface amine.

ABSTRACTThe kinetics of formanilides hydrolysis were determined under first‐order conditions in hydrochloric acid (0.01–8 M, 20–60°C) and in hydroxide solutions (0.01–3 M, 25 and 40°C). Under acidic conditions, second‐order specific acid catalytic constants were used to construct Hammett plots. The ortho effect was analyzed using the Fujita–Nishioka method. In alkaline solutions, hydrolysis displayed both first‐ and second‐order dependence in the hydroxide concentration. The specific base catalytic constants were used to construct Hammett plots. Ortho effects were evaluated for the first‐order dependence on the hydroxide concentration. Formanilide hydrolyzes in acidic solutions by specific acid catalysis, and the kinetic study results were consistent with the AAC2 mechanism. Ortho substitution led to a decrease in the rates of reaction due to steric inhibition of resonance, retardation due to steric bulk, and through space interactions. The primary hydrolytic pathway in alkaline solutions was consistent with a modified BAC2 mechanism. The Hammett plots for hydrolysis of meta‐ and para‐substituted formanilides in 0.10 M sodium hydroxide solutions did not show substituent effects; however, ortho substitution led to a decrease in rate constants proportional to the steric bulk of the substituent.

The aggregation behavior and critical aggregation concentration (CAC) values of daptomycin in aqueous solutions were evaluated under the external factors of pH, temperature, daptomycin concentration, and calcium ions concentration by using the complementary characterization techniques, fluorescence, dynamic and static light scattering, and nuclear magnetic resonance (NMR) spectroscopy. On the basis of the intrinsic fluorescence resonance energy transfer of daptomycin, the CAC values were identified by an upward inflection of the fluorescence emission from Kyn-13 at 460 nm. The pH-dependent CAC values were determined to be 0.14 mM at pH 3.0, 0.12 mM at pH 4.0, and 0.20 mM at pH 2.5 and 5.0. The CAC values obtained by fluorescence spectroscopy were confirmed by dynamic light scattering and NMR spectroscopy.

Solid-state NMR spectroscopy (SSNMR), coupled with powder X-ray diffraction (PXRD), was used to identify the physical forms of gabapentin in samples prepared by recrystallization, spray drying, dehydration, and milling. Four different crystalline forms of gabapentin were observed: form I, a monohydrate, form II, the most stable at ambient conditions, form III, produced by either recrystallization or milling, and an isomorphous desolvate produced from desolvating the monohydrate. As-received gabapentin (form II) was ball-milled for 45 min in both the presence and absence of hydroxypropylcellulose (HPC). The samples were then stored for 2 days at 50°C under 0% relative humidity and analyzed by 13 C SSNMR and PXRD. High-performance liquid chromatography was run on the samples to determine the amount of degradation product formed before and after storage. The 1 H T 1 values measured for the sample varied from 130 s for the as-received unstressed material without HPC to 11 s for the material that had been ball-milled in the presence of HPC. Samples with longer 1 H T 1 values were substantially more stable than samples that had shorter T 1 values. Samples milled with HPC had detectable form III crystals as well. These results suggest that SSNMR can be used to predict gabapentin stability in formulated products.

The objectives of the studies presented herein were to determine the pH-dependent chlorhexidine (CHD) degradation scheme, to determine the rate laws, and to propose reasonable mechanisms for CHD hydrolysis in aqueous solutions. A series of degradation kinetic studies was conducted at 90.0 °C using reaction mixtures containing 0.10 mM CHD prepared in the pH range of 0.5-9.0 using hydrochloric acid, sodium hydroxide, acetate, phosphate, or 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid buffers at a constant ionic strength of 0.500 M. Concentration-time profiles for all degradation products, intermediates, and substrates were determined by high-performance liquid chromatography (HPLC). Degradation products and intermediates were identified using a combination of liquid chromatography-mass spectrometry, kinetic analysis, and HPLC comparison with authentic compounds. pH-dependent degradation scheme and rate laws were parameterized using nonlinear regression. The direct formation of p-chloroaniline (PCA) from CHD is the major pathway in acidic conditions, whereas the indirect formation of PCA via the formation of p-chlorophenylurea is the main pathway in alkaline conditions.

Gabapentin degrades directly to gabapentin-lactam (gaba-L) in the solid state. The objective of this study was to formulate a drug degradation model that accounted for the environmental storage conditions and mechanical stress (prior to storage) on lactamization kinetics. The effects of mechanical stress on drug degradation kinetics were determined by milling gabapentin in a FRITSCH Planetary Micro Mill for 0 and 60min. The resultant gabapentin powder was stored at 40°C–60°C and 5%–30% relative humidity. The rate of gaba-L formation was measured by high-performance liquid chromatography. An irreversible two-step autocatalytic reaction scheme was fit using nonlinear regression methods. The resultant kinetic model was used to predict the time-dependent concentration of degradant of gabapentin tablets prepared under various exemplary manufacturing conditions, thereby demonstrating the ability of the model to link manufacturing variation and chemical stability in solid-state gabapentin formulations.

The FDA's Quality by Design initiative and associated design space construct (ICH, 2009), have stimulated the use of quantitative methods, mathematical and statistical models, and designed experiments in the process of drug development and manufacture.For a given drug product, the design space may be interpreted as the constrained region of the manufacturing operating variable space within which assurance can be provided that drug product quality specifications will be met.It is now understood, at least conceptually, that this assurance is not deterministic, rather it must be stated in probabilistic terms.In this paper, we report on the use of Bayesian methods to develop a suitable risk metric based on both mathematical and statistical models of the manufacturing processes and product properties.The Bayesian estimation is carried out to determine the joint posterior distribution of the probability of the product meeting quality specifications.The computations are executed using a novel Variational Bayes approximation.In this paper the direct computational approach using this approximation is compared to the widely used but computationally very intensive Markov Chain Monte Carlo method.The approach is illustrated using experimental data and models drawn from a recent QbD study on the drug gabapentin in which the authors were participants.