Saddle-Reset for Robust Parameter Estimation and Identifiability Analysis of Nonlinear Mixed Effects Models.

Parameter estimation of a nonlinear model based on maximizing the likelihood using gradient-based numerical optimization methods can often fail due to premature termination of the optimization algorithm. One reason for such failure is that these numerical optimization methods cannot distinguish between the minimum, maximum, and a saddle point; hence, the parameters found by these optimization algorithms can possibly be in any of these three stationary points on the likelihood surface. We have found that for maximization of the likelihood for nonlinear mixed effects models used in pharmaceutical development, the optimization algorithm Broyden-Fletcher-Goldfarb-Shanno (BFGS) often terminates in saddle points, and we propose an algorithm, saddle-reset, to avoid the termination at saddle points, based on the second partial derivative test. In this algorithm, we use the approximated Hessian matrix at the point where BFGS terminates, perturb the point in the direction of the eigenvector associated with the lowest eigenvalue, and restart the BFGS algorithm. We have implemented this algorithm in industry standard software for nonlinear mixed effects modeling (NONMEM, version 7.4 and up) and showed that it can be used to avoid termination of parameter estimation at saddle points, as well as unveil practical parameter non-identifiability. We demonstrate this using four published pharmacometric models and two models specifically designed to be practically non-identifiable.

A cross-industry forum on benchmarking critical quality attribute identification and linkage to process characterization studies.

Identification of Critical Quality Attributes (CQAs) and subsequent characterization in process development studies are the key elements of quality by design (QbD) for biopharmaceutical products. Since the inception of ICH Q8R2, several articles have been published on approaches to conducting CQA risk assessments as well as the application to process understanding. A survey was conducted by multiple companies participating in an International Consortium working group on the best practices for identifying CQAs with linkages to process characterization (PC) studies. The results indicate that the companies surveyed are using similar approaches/timing to identify CQAs during process development. Consensus was also observed among the companies surveyed with approaches to linkage of CQAs to process characterization studies leading to impact to control strategies and lifecycle management.

Enhancing reaction-based de novo design using a multi-label reaction class recommender.

Reaction-based de novo design refers to the in-silico generation of novel chemical structures by combining reagents using structural transformations derived from known reactions. The driver for using reaction-based transformations is to increase the likelihood of the designed molecules being synthetically accessible. We have previously described a reaction-based de novo design method based on reaction vectors which are transformation rules that are encoded automatically from reaction databases. A limitation of reaction vectors is that they account for structural changes that occur at the core of a reaction only, and they do not consider the presence of competing functionalities that can compromise the reaction outcome. Here, we present the development of a Reaction Class Recommender to enhance the reaction vector framework. The recommender is intended to be used as a filter on the reaction vectors that are applied during de novo design to reduce the combinatorial explosion of in-silico molecules produced while limiting the generated structures to those which are most likely to be synthesisable. The recommender has been validated using an external data set extracted from the recent medicinal chemistry literature and in two simulated de novo design experiments. Results suggest that the use of the recommender drastically reduces the number of solutions explored by the algorithm while preserving the chance of finding relevant solutions and increasing the global synthetic accessibility of the designed molecules.

Quo Vadis qNMR?

The quantification of a drug, its impurities, and e.g. components of a mixture has become routine in NMR laboratories and many applications have been described in the literature. However, besides simply using 1D 1H or 13C NMR, a number of more advanced methods has been developed and used in the past. Here, we want to describe the applicability of nuclei beyond the classical ones 1H and 13C. Mixtures can be characterized much better by applying various chemometric methods and separating the signals of mixture components can be achieved by DOSY experiments. All these methods contribute to the platform of qNMR methods and extend the possibilities of NMR for quantification and quality evaluation of drugs, excipients, polymers, and plant extracts. However, for quantification purposes, validation is always an issue and it is necessary to think about taking NMR related measures which might be different from the ones considered for chromatographic methods.

Regulatory assessment of drug dissolution profiles comparability via maximum deviation.

In drug development, comparability of dissolution profiles of 2 different formulations is usually assessed using the similarity factor f2 . In practice, the drug dissolution profiles are deemed similar if the f2 exceeds 50, which occurs when a 10% maximum difference in the mean percentage of the dissolved drug at each time point between test and reference formulation is obtained. According to the Guideline on the Investigation of Bioequivalence (CPMP/EWP/QWP/1401/98 Rev. 1/ Corr **) use of the f2 is however restricted by a set of validity conditions. If some of these conditions are not satisfied, the f2 is not considered suitable, and alternative statistical methods are needed. In this article, we propose an inferential framework based on the maximum deviation between curves to test the comparability of drug dissolution profiles. The new methodology is applicable regardless whether the validity criteria of the f2 are met or not. Contrary to the f2 , this approach also integrates the variability of the measurements over time and not only their average. To benchmark our method, we performed simulations informed by 3 real case studies provided by the European Medicines Agency and extracted from dossiers submitted to the Centralised Procedure for Marketing Authorisation Application. In the scenarios of the simulation study, the new method controlled its type I error rate when the maximum deviation was greater than the similarity acceptance limit of 10%. The power exceeded 80% for small values of the maximum deviation, while the test was more conservative for intermediate ones. Our results were also very robust to sampling variations. Based on these positive findings, we encourage applicants to consider the new maximum deviation-based method as a valid alternative to the f2 , especially when the validity criteria of the latter are not met.

Learning Medicinal Chemistry Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) Rules from Cross-Company Matched Molecular Pairs Analysis (MMPA).

The first large scale analysis of in vitro absorption, distribution, metabolism, excretion, and toxicity (ADMET) data shared across multiple major pharma has been performed. Using advanced matched molecular pair analysis (MMPA), we combined data from three pharmaceutical companies and generated ADMET rules, avoiding the need to disclose the full chemical structures. On top of the very large exchange of knowledge, all companies involved synergistically gained approximately 20% more rules from the shared transformations. There is good quantitative agreement between the rules based on shared data compared to both individual companies' rules and rules published in the literature. Known correlations between log  D, solubility, in vitro clearance, and plasma protein binding also hold in transformation space, but there are also interesting exceptions. Data pools such as this allow focusing on particular functional groups and characterizing their ADMET profile. Finally the role of a corpus of robustly tested medicinal chemistry knowledge in the training of medicinal chemistry is discussed.

Comparison of Dissolution Similarity Assessment Methods for Products with Large Variations: f2 Statistics and Model-Independent Multivariate Confidence Region Procedure for Dissolution Profiles of Multiple Oral Products.

The current Japanese Ministry of Health Labour and Welfare (MHLW)'s Guideline for Bioequivalence Studies of Generic Products uses averaged dissolution rates for the assessment of dissolution similarity between test and reference formulations. This study clarifies how the application of model-independent multivariate confidence region procedure (Method B), described in the European Medical Agency and U.S. Food and Drug Administration guidelines, affects similarity outcomes obtained empirically from dissolution profiles with large variations in individual dissolution rates. Sixty-one datasets of dissolution profiles for immediate release, oral generic, and corresponding innovator products that showed large variation in individual dissolution rates in generic products were assessed on their similarity by using the f2 statistics defined in the MHLW guidelines (MHLW f2 method) and two different Method B procedures, including a bootstrap method applied with f2 statistics (BS method) and a multivariate analysis method using the Mahalanobis distance (MV method). The MHLW f2 and BS methods provided similar dissolution similarities between reference and generic products. Although a small difference in the similarity assessment may be due to the decrease in the lower confidence interval for expected f2 values derived from the large variation in individual dissolution rates, the MV method provided results different from those obtained through MHLW f2 and BS methods. Analysis of actual dissolution data for products with large individual variations would provide valuable information towards an enhanced understanding of these methods and their possible incorporation in the MHLW guidelines.

Characterizing the Overall Derivatization of Conjugated Oligomeric Proteins.

The analysis and accurate quantitation of bioconjugations proves challenging in the case of oligomeric proteins, especially when the size of the molecule or the nature of the conjugate do not allow the analysis of the intact protein under native conditions. In this case, analytical methods are frequently applied that result in a dissociation of non-covalently linked subunits. This limits the analysis to a description of individual subunits, thereby obscuring the accurate characterization of the overall functionalization. This situation is frequently encountered in the biopharmaceutically important case of protein PEGylation, as the biophysical properties of the PEG polymer generally make analysis and accurate quantitation for a protein with multiple conjugation sites challenging under native conditions. In this work we present a statistical measure for deriving the overall functionalization of an oligomeric protein from the data obtained from readily accessible assays that cause non-covalently associated subunits to dissociate. This approach is broadly applicable for the characterization and optimization of bioconjugation reactions for multimeric biomolecules. It should also be highly valuable for the accurate description of composition and manufacturing consistency of conjugated biotherapeutics in regulatory filings.LAY ABSTRACT: Conjugated proteins are an important class of biopharmaceuticals. For these molecules, successful drug development requires accurate methods for the quantitative characterization of protein conjugation. This task is particularly challenging in the case of proteins consisting of several, non-covalently linked subunits, especially when the size of the protein or nature of the conjugate do not allow for analysis of the intact oligomeric molecule. Many of the analytical methods used to characterize these conjugates, such as reverse phase high-performance liquid chromatography, cause the individual subunits to dissociate, making it difficult to fully understand quality attributes at the native oligomeric level. We present a method to accurately quantify the overall conjugation of an oligomeric protein in these cases when readily available assays describe only individual subunits. This should be highly valuable for process optimization and to correctly characterize the conjugated biopharmaceutical in interactions with regulatory agencies.

Mathematical model to analyze the dissolution behavior of metastable crystals or amorphous drug accompanied with a solid-liquid interface reaction.

Metastable crystals and the amorphous state of poorly water-soluble drugs in solid dispersions (SDs), are subject to a solid-liquid interface reaction upon exposure to a solvent. The dissolution behavior during the solid-liquid interface reaction often shows that the concentration of drugs is supersaturated, with a high initial drug concentration compared with the solubility of stable crystals but finally approaching the latter solubility with time. However, a method for measuring the precipitation rate of stable crystals and/or the potential solubility of metastable crystals or amorphous drugs has not been established. In this study, a novel mathematical model that can represent the dissolution behavior of the solid-liquid interface reaction for metastable crystals or amorphous drug was developed and its validity was evaluated. The theory for this model was based on the Noyes-Whitney equation and assumes that the precipitation of stable crystals at the solid-liquid interface occurs through a first-order reaction. Moreover, two models were developed, one assuming that the surface area of the drug remains constant because of the presence of excess drug in the bulk and the other that the surface area changes in time-dependency because of agglomeration of the drug. SDs of Ibuprofen (IB)/polyvinylpyrrolidone (PVP) were prepared and their dissolution behaviors under non-sink conditions were fitted by the models to evaluate improvements in solubility. The model assuming time-dependent surface area showed good agreement with experimental values. Furthermore, by applying the model to the dissolution profile, parameters such as the precipitation rate and the potential solubility of the amorphous drug were successfully calculated. In addition, it was shown that the improvement in solubility with supersaturation was able to be evaluated quantitatively using this model. Therefore, this mathematical model would be a useful tool to quantitatively determine the supersaturation concentration of a metastable drug from solid dispersions.

Age-appropriate and acceptable paediatric dosage forms: Insights into end-user perceptions, preferences and practices from the Children's Acceptability of Oral Formulations (CALF) Study.

A lack of evidence to guide the design of age-appropriate and acceptable dosage forms has been a longstanding knowledge gap in paediatric formulation development. The Children's Acceptability of Oral Formulations (CALF) study captured end-user perceptions and practices with a focus on solid oral dosage forms, namely tablets, capsules, chewables, orodispersibles, multiparticulates (administered with food) and mini-tablets (administered directly into the mouth). A rigorous development and testing phase produced age-adapted questionnaires as measurement tools with strong evidence of validity and reliability. Overall, 590 school children and adolescents, and 428 adult caregivers were surveyed across hospitals and various community settings. Attitudes towards dosage forms primarily differed based on age and prior use. Positive attitudes to tablets and capsules increased with age until around 14 years. Preference was seen for chewable and orodispersible preparations across ages, while multiparticulates were seemingly less favourable. Overall, 59.6% of school children reported willingness to take 10mm diameter tablets, although only 32.1% of caregivers perceived this size to be suitable. While not to be taken as prescriptive guidance, the results of this study provide some evidence towards rational dosage form design, as well as methodological approaches to help design tools for further evaluation of acceptability within paediatric studies.

Theoretical Analysis of Drug Dissolution: I. Solubility and Intrinsic Dissolution Rate.

The first-principles approach presented in this work combines surface kinetics and convective diffusion modeling applied to compounds with pH-dependent solubility and in different dissolution media. This analysis is based on experimental data available for approximately 100 compounds of pharmaceutical interest. Overall, there is a linear relationship between the drug solubility and intrinsic dissolution rate expressed through the total kinetic coefficient of dissolution and dimensionless numbers defining the mass transfer regime. The contribution of surface kinetics appears to be significant constituting on average ∼20% resistance to the dissolution flux in the compendial rotating disk apparatus at 100 rpm. The surface kinetics contribution becomes more dominant under conditions of fast laminar or turbulent flows or in cases when the surface kinetic coefficient may decrease as a function of solution composition or pH. Limitations of the well-known convective diffusion equation for rotating disk by Levich are examined using direct computational modeling with simultaneous dissociation and acid-base reactions in which intrinsic dissolution rate is strongly dependent on pH profile and solution ionic strength. It is shown that concept of diffusion boundary layer does not strictly apply for reacting/interacting species and that thin-film diffusion models cannot be used quantitatively in general case.

Design and optimization of disintegrating pellets of MCC by non-aqueous extrusion process using statistical tools.

The objective of the study was to design and optimize a disintegrating pellet formulation of microcrystalline cellulose by non-aqueous extrusion process for a water sensitive drug using various statistical tools. Aspirin was used as a model drug. Disintegrating matrix pellets of aspirin using propylene glycol as a non-aqueous granulation liquid and croscarmellose as a disintegrant was developed. Plackett-Burman design was initially conducted to screen and identify the significant factors. Final optimization of formula was performed by response surface methodology using a central composite design. The critical attributes of the pellet dosage forms (dependent variables); disintegration time, sphericity and yield were predicted with adequate accuracy based on the regression model. Pareto charts and contour charts were studied to understand the influence of factors and predict the responses. A design space was constructed to meet the desirable targets of the responses in terms of disintegration time <5min, maximum yield, sphericity >0.95 and friability <1.7%. The optimized matrix pellets were enteric coated using Eudragit L 100. The drug release from the enteric coated pellets after 30min in the basic media was ~93% when compared to ~77% from the marketed pellets. The delayed release pellets stored at 25°C/60% RH were stable for a period of 10mo. In conclusion, it can be stated that the developed process for disintegrating pellets using non-aqueous granulating agents can be used as an alternative technique for various water sensitive drugs, circumventing the application of volatile organic solvents in conventional drug layering on inert cores. The scope of this study can be further extended to hydrophobic drugs, which may benefit from the rapid disintegration property and the use of various hydrophilic excipients used in the optimized pellet formulation to enhance dissolution and in turn improve bioavailability.

Use of similarity scoring in the development of oral solid dosage forms.

In the oral solid dosage form space, material physical properties have a strong impact on the behaviour of the formulation during processing. The ability to identify materials with similar characteristics (and thus expected to exhibit similar behaviour) within the company's portfolio can help accelerate drug development by enabling early assessment and prediction of potential challenges associated with the powder properties of a new active pharmaceutical ingredient. Such developments will aid the production of robust dosage forms, in an efficient manner. Similarity scoring metrics are widely used in a number of scientific fields. This study proposes a practical implementation of this methodology within pharmaceutical development. The developed similarity metrics is based on the Mahalanobis distance. Scanning electron microscopy was used to confirm morphological similarity between the reference material and the closest matches identified by the metrics proposed. The results show that the metrics proposed are able to successfully identify material with similar physical properties.

The impact of data integrity on decision making in early lead discovery.

Data driven decision making is a key element of today's pharmaceutical research, including early drug discovery. It comprises questions like which target to pursue, which chemical series to pursue, which compound to make next, or which compound to select for advanced profiling and promotion to pre-clinical development. In the following paper we will exemplify how data integrity, i.e. the context data is generated in and auxiliary information that is provided for individual result records, can influence decision making in early lead discovery programs. In addition we will describe some approaches which we pursue at Boehringer Ingelheim to reduce the risk for getting misguided.

Lost interest for existing compounds: New boosts.

Development of new drugs is typically thought of as a bottom-up endeavor where basic science identifies a target, various strategies are used to generate drugs that stimulate or inhibit the target, the drugs are first tested for safety and efficacy in animals and finally efficacy and safety are evaluated in a well defined clinical development process. However, this is not the only way that new drug products are developed. Many new products come from re-initiating development of discontinued drugs, finding new uses for existing drugs, creating a new product by obtaining marketing approval in expanded territories, obtaining approvals for new formulations or a single isomer of a previously approved racemic drug, converting products from prescription to over-the- counter use or converting folk medicines or vitamins to modern pharmaceuticals. Based on this long and successful history of contributions to modern therapeutics, these alternative sources of new products should not be neglected.

More than just crushing: a prospective pre-post intervention study to reduce drug preparation errors in patients with feeding tubes.

WHAT IS KNOWN AND OBJECTIVES: Incorrect drug preparation for patients with feeding tubes can result in harm for the patient and the preparing person. Combined intervention programs are effective tools to reduce such preparation errors. However, to date, intervention programs have been mostly tested in hospitals with computerized physician order entry (CPOE), unit-dose systems, or ward-based clinical pharmacists. Hence, the primary objective of this study was to develop and evaluate an intervention program tailored to hospitals without such preconditions. METHODS: We conducted a prospective pre-/post-intervention study on a gastroenterological intensive care unit (ICU) and a surgical ward for oral, dental and maxillofacial diseases (surgical ward). During the study periods, observers documented and evaluated drug preparation processes of all peroral drugs for patients with feeding tubes. The primary endpoint was the rate of inappropriately crushed and/or suspended solid peroral drugs in regards to all solid peroral drugs. RESULTS AND DISCUSSION: Altogether, we evaluated 775 drug preparation processes of solid peroral drugs on the ICU and 975 on the surgical ward. The intervention program significantly reduced incorrect crushing and/or suspending of solid peroral drugs for administration to patients with feeding tubes from 9·8% to 4·2% (P < 0·01) on the ICU and from 5·7% to 1·4% (P < 0·01) on the surgical ward. WHAT IS NEW AND CONCLUSION: The implementation of the newly developed intervention program significantly reduced the rate of inappropriately prepared solid peroral drugs, suggesting that it is an effective measure to enable safe drug administration for inpatients with feeding tubes.

Use of injectable drugs with oral-formulation alternatives for outpatients in South Korea.

This study analyzed the use of injectable drugs with oral-formulation alternatives in the outpatient setting in South Korea. We conducted a retrospective cross-sectional data analysis using 2008 National Health Insurance claims data. All active ingredients were categorized into dual-formulation ingredients (DFIs) and single formulation ingredients (SFIs), and were identified by the type of healthcare service provider (HSP) and anatomical therapeutic chemical (ATC) group. 14.6 % (102/701) of total drugs were extracted as DFIs at about the same rate as that for drugs in the World Health Organization database (14.45 %), showing similar patterns by ATC group. The rate of injectable drug use varied more substantially for DFIs (range 0.94-4.54 %) than for SFIs (range 0.27-1.12 %) by the type of HSP. For DFIs, the highest proportion of injectable drug use was observed in group H (all hormonal preparations, 22.74 %) and group M (anti-inflammatory and anti-rheumatic preparations, 10.23 %) among ATC groups. The proportion of injectable drug use was higher in clinics and small hospitals than in tertiary hospitals and general hospitals where patients with more severe cases tend to visit. The results imply the potentially inappropriate or excessive use of injectable drugs and suggest the need to develop standard guidelines for injectable drug use and strategies to promote high-quality healthcare including education on rational prescribing.