AAPS Journal最新文献

A co-processed active pharmaceutical ingredient (CP API) is the combination of an active pharmaceutical ingredient (API) with non-active component(s). This technology has been demonstrated to offer numerous benefits, including but not limited to improved API properties and stability. The infrastructure requirements are such that the manufacture of a CP API is typically best suited for an API facility. CP API has been regulated as either an API or as a drug product intermediate (DPI). This variability in the designation has led to ambiguities on the regulatory CMC expectations in the CP API including the stability of CP API and CP API containing products which, in turn has hampered the broader application of this technology in the pharmaceutical industry. This difference in designation also resulted in challenges to the lifecycle management of the regulatory documentation for the CMC information of the CP API.This white paper represents the proposals for the regulatory requirements on stability studies related to CP API and to drug product containing CP API by the CP API Working Group (WG) of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ). Additionally, considerations and the WG's recommendations on the stability studies of CP API from different manufacturing sites or processes and post-approval changes for product containing CP API are described.

Duplicate pharmacokinetic profiles in bioequivalence trials is an issue which has caused hundreds of retracted marketing authorizations. No formal test for profile duplication exists in spite of the existence of profile comparison algorithms, so defining a threshold that distinguishes a naturally occurring pair from a duplication remains difficult. An idea called ISPR (incurred subject period analysis) was aired in 2023 and is evaluated in this paper along with three new profile comparison methods. ISPR involves analysis of entire PK-profiles within a study. It is shown that when ISPR is combined with appropriate PK-profile comparison methods, the duplicate pairs display a lower score (better similarity) than pair that do not arise out of duplication. Therefore, ISPR may help establish a threshold that distinguishes fraudulent profile pairs from non-fraudulent profile pairs. ISPR therefore may be used as QA tool, serves as a method by which a CRO can -to some extent- show that their studies do not contain duplicates in the primary analysis, and thus also may be a means by which sponsor can argue that their studies are trustworthy, in case the suspicion about duplication arises. This paper does not introduce a formal test for this type of fraud; rather the authors see it as a first moderate step in that direction. Hopefully, if or when ISPR data is submitted to authorities as part of general dossier submission, data will accumulate to the extent that they may be able to develop models that allow formal testing for profile duplication.

An enzyme-linked immunosorbent assay (ELISA) based anti-drug antibody (ADA) assay was developed to support the clinical development of a bispecific antibody biotherapeutic anti-A/B. This anti-A/B clinical ADA Version 1 (V1) assay was successfully validated initially using commercial samples from the target indication. However, applying the validation cut point factors (CPFs) led to a high untreated ADA positive rate in the Phase 1 study baseline sample analysis. While implementing the in-study CPFs was effective to mitigate the high baseline prevalence, this led to unfavorable assay sensitivity with no drug tolerance, which necessitated an assay re-optimization. The re-optimized Version 2 assay (V2) was able to mitigate the matrix interference observed in the clinical sample testing using the V1 assay, proven to be a more suitable method. The V2 assay optimization work was discussed, and the performance of the V1 and V2 assays during validation and clinical sample analysis was compared. Preliminary sample testing results generated using the two versions of the assay were compared and the ADA clinical impact was discussed. Our experience insinuates that a successfully validated method does not guarantee to be appropriate for sample testing. Adjustments of the method may be required to ensure that it performs as expected during sample testing and throughout the assay's lifecycle. This work highlights the importance of verifying the assay suitability during clinical sample testing and making appropriate adjustments as needed, especially in the first clinical study and the first study for a new indication.

Accurate prediction of drug-drug interactions (DDI) from in vitro data is important, as it provides insights on clinical DDI risk and study design. Historically, the lower limit of plasma fraction unbound (f_u,p) is set at 1% for DDI prediction of highly bound compounds by the regulatory agencies due to the uncertainty of the f_u,p measurements. This leads to high false positive DDI predictions for highly bound compounds. The recently published ICH M12 DDI guideline allows the use of experimental f_u,p for DDI prediction of highly bound compounds. To further build confidence in DDI prediction of highly bound compounds using experimental f_u,p values, we evaluated a set of drugs with f_u,p < 1% and clinical DDI > 20% using both basic and mechanistic static models. All the compounds evaluated were flagged for DDI risk with the mechanistic model using experimental f_u,p values. There was no false negative DDI prediction. Similarly, using the basic model, the DDI risk of all the compounds was identified except for CYP2D6 inhibition of almorexant. The totality of the data demonstrates that the DDI potential of highly bound compounds can be predicted accurately when actual protein binding numbers are measured.

The ADA testing strategy for protein therapeutics was established almost two decades ago when assay methodologies were rudimentary, and serious immunogenicity-related safety issues had recently been observed with some biotherapeutics. The current testing paradigm employs multiple tiers and stringent cut points to minimize false negatives, reflecting a conservative stance towards ADA analysis. The development of highly sensitive ADA assay platforms and technologies such as humanized or fully human monoclonal antibody (mAb) drugs has put the traditional, resource-intensive 3-tiered testing approach under scrutiny. ADA data from clinical studies for three different mAb programs were re-assessed to explore the feasibility of a simplified 1-tiered ADA testing strategy with a 1% false positive cut point versus the traditional 3-tiered approach. The analysis demonstrated moderate to strong correlations between screening results (signal-to-noise, S/N) and those of confirmation and titer results, with the vast majority of samples (~ 97%) across all studies having the same ADA positive/negative classification with either testing approach. Furthermore, at the subject level, over 92% had the same ADA category (pre-existing, treatment-emergent, treatment-boosted) under both testing approaches. The re-categorized subjects had low titer ADA responses with no observed clinical implications on pharmacokinetics, efficacy, or safety. Finally, the treatment-emergent ADA incidences were comparable between the 1-tiered and 3-tiered approaches. The results demonstrate that the 1-tiered testing strategy is suitable for ADA assessment in these programs and is likely more widely applicable. Additionally, the 1-tiered approach could expedite data delivery and reduce resource needs in clinical development without compromising data quality or clinical interpretation.

Accurate measurement of plasma protein binding (PPB) is of critical importance in drug discovery. Methodologies for PPB measurement continue to evolve to address the challenges of highly bound compounds. In order to generate high quality PPB data, it is crucial to not only apply state-of-the-art methods and highly sensitive and selective detectors, but also use high-quality plasma. In this study, we found that plasticizers, leaching from polyvinyl chloride (PVC) plasma storage bags, interfered with drug binding to both human α1-acid glycoprotein (AAG) and human serum albumin (HSA). Several AAG and HSA binding drugs were used to probe the differences in PPB using blood/plasma collected and stored in PVC bags or glass tubes through vacutainers. The results showed that plasma collected using vacutainers into the glass tubes has lower plasma fraction unbound (f_u,p) values than those from the PVC bags. The f_u,p differences can be as high as 32-fold. Hence, it is recommended to use vacutainers and glass tubes rather than PVC bags, for blood collection and plasma storage. Plasma from animal species collected using polypropylene syringes into polyethylene tubes showed no differences in f_u,p from plasma collected using vacutainers into glass tubes. Not all compounds are sensitive to plasticizer interference for PPB. It is therefore important to select appropriate positive controls for f_u,p measurement, such as warfarin for HSA and imatinib for AAG, to monitor the quality of plasma and minimize the interference from plasticizers.

Amorphous solid dispersions (ASDs) represent a promising strategy for enhancing the solubility of poorly soluble drugs. However, the mechanisms underlying the physical stability of ASDs remain insufficiently understood. This study aims to investigate these mechanisms and propose quantitative thresholds to predict the maximum stable drug loading using molecular dynamics simulations. Poly(vinylpyrrolidone) (PVP) and poly (vinylpyrrolidone-co-vinyl acetate) (PVPVA64) are selected as polymeric carriers, while naproxen and acetaminophen serve as model drugs, resulting in the formulation of 18 distinct ASDs across four types for comparison with experimental results. Our findings indicate that the molecular mobility of active pharmaceutical ingredients (APIs) is the primary determinant of solid dispersion stability. High polymer concentrations limit drug molecular mobility through spatial structural constraints and ASD viscosity. As drug loading increases, the polymer concentration reaches a critical threshold (C*), beyond which drug-rich regions form, leading to potential aggregation, rearrangement, and recrystallization of drug molecules into more energetically stable forms. Notably, both the interaction energy and diffusion coefficient show sharp fluctuations at the maximum stable drug loading, which can serve as predictive indicators for ASD stability. Additionally, a search strategy is used to identify potential pre-crystalline sites. By integrating kinetic, thermodynamic, and pre-crystalline analyses through molecular dynamics simulations, this study provides a foundation for more accurate predictions of ASD stability, significantly aiding future formulation development.

Recognizing the approach of a dramatic expansion of peptide therapeutics reaching the marketplace in recent years, led by GLP-1 receptor agonists such as semaglutide and liraglutide, the Center for Drug Evaluation and Research (CDER) branch of the US Food and Drug Administration (FDA) issued a final guidance in 2021 that was intended to assist generic drug producers in meeting Abbreviated New Drug Application (ANDA) obligations to establish "sameness" of their active peptide drug relative to that produced by innovator companies. Research and a published report by FDA scientists on best practices followed, which promulgated the use of nuclear magnetic resonance (NMR) and principal component analysis (PCA) and established a quantitative standard by which "sameness" of higher order structure for the applicant's peptide drug could be judged. A key requirement is that drug product samples be analyzed directly and non-invasively, a condition which in practice restricts sample modification to the addition of a small amount of deuterium oxide to allow signal lock and spectral data alignment (as required for NMR analysis). In the study described herein, data are presented to illustrate that 1) relatively small differences in sample pH can cause significant shifting of certain proton resonances, 2) that such resonance shifting is readily reversible and due to the degree of protonation of specific amino acid residues (rather than reflecting differences in higher order structure), and 3) that small differences in pH variability between sample cohorts can frequently cause failure to meet the quantitative benchmark established by the agency. Methodology is presented by which drug sample pHs can be aligned with minimal impact, and a recommendation is made that minor sample pH adjustments be allowed in assessing "sameness" of peptide drug higher order structure.

The development of advanced preclinical models is crucial for the evaluation and validation of novel therapeutic strategies in oncology. Three-dimensional (3D) microtumor models, which incorporate both cancer and stromal cells within biomimetic hydrogels, have emerged as powerful tools that more accurately replicate the complex tumor microenvironment compared to traditional two-dimensional (2D) cell culture systems. In this context, our study aims to develop 3D microtumor models by integrating cancer and stromal cells within an extracellular-matrix-mimetic hydrogel, as a physiologically accurate microtumor model that can serve as an innovative platform for advanced cancer research and drug screening. Microtumors composed of varying ratios of leukemia cells (HL-60) to healthy ovarian stromal cells (SCs) (1:1, 1:10, 1:100, or 1:1000) were encapsulated in PEGylated fibrin hydrogel and cultured for 5 days. The proliferation and dynamics of cancerous and healthy cell populations were evaluated using CD43/Ki67 immunofluorescence double staining. Our findings indicate that tumor development and malignancy progression can be influenced by adjusting cell culture ratios and incubation time. Notably, the HL-60:SCs ratio of 1:100 closely replicated leukemia cell invasion in ovarian tissue, demonstrating detectable malignancy on the third and fifth days without significant changes in total cell density dynamics. This 3D leukemia microtumor model offers superior physiological relevance compared to traditional 2D in vitro assays and shows promising potential for applications in cellular analysis and drug screening.