Development of Quantitative Comparative Approaches to Support Complex Generic Drug Development.

On October 27-28, 2022, the US Food and Drug Administration (FDA) and the Center for Research on Complex Generics (CRCG) hosted a virtual public workshop titled "Best Practices for Utilizing Modeling Approaches to Support Generic Product Development." This report summarizes the presentations and panel discussions for a session titled "Development of Quantitative Comparative Approaches to Support Complex Generic Drug Development." This session featured speakers and panelists from both the generic industry and the FDA who described applications of advanced quantitative approaches for generic drug development and regulatory assessment within three main topics of interest: (1) API sameness assessment for complex generics, (2) particle size distribution assessment, and (3) dissolution profile similarity comparison. The key takeaways were that the analysis of complex data poses significant challenges to the application of conventional statistical bioequivalence methods, and there are various opportunities for using data analytics approaches for developing and applying suitable equivalence assessment method.

In vitro dissolution profile comparison using bootstrap bias corrected similarity factor, f2.

In vitro dissolution profile has been shown to be correlated with the drug absorption and has often been considered as a metric for assessing in vitro bioequivalence between a test product and corresponding reference one. Various methods have been developed to assess the similarity between two dissolution profiles. In particular, similarity factor f2 has been reviewed and discussed extensively in many statistical articles. Although the f2 lacks inferential statistical properties, the estimation of f2 and its various modified versions were the most widely used metric for comparing dissolution profiles. In this paper, we investigated performances of the naive f2 estimate method, bootstrap f2 confidence interval method and bias corrected-accelerated (BCa) bootstrap f2 confidence interval method for comparing dissolution profiles. Our studies show that naive f2 estimate method and BCa bootstrap f2 confidence interval method are unable to control the type I error rate. The bootstrap f2 confidence interval method can control the type I error rate under a specific level. However, it will cause great conservatism on the power of the test. To solve the potential issues of the previous methods, we recommended a bootstrap bias corrected (BC) f2 confidence interval method in this paper. The type I error rate, power and sensitivity among different f2 methods were compared based on simulations. The recommended bootstrap BC f2 confidence interval method shows better control of type I error than the naive f2 estimate method and BCa bootstrap f2 confidence interval method. It also provides better power than the bootstrap f2 confidence interval method.

MicroRNA-143-3p ameliorates collagen-induced arthritis by polarizing naive CD4+ T cells into Treg cells.

BACKGROUND: Rheumatoid arthritis (RA) is a persistent and systemic autoimmunity disease. The abnormal differentiation of Treg cells is important in pathogenesis. Despite previous studies showed that microRNAs (miRNAs, miR) are pivotal modulators of Treg cells, the effect of miRNAs on Treg cell differentiation and function is not clear. Our study wants to reveal the relationship of miR-143-3p with the differentiative ability and biofunction of Treg cells during the development of RA. METHODS: The Expressing level of miR-143-3p and cell factor generation in peripheral blood (PB) of RA sufferers were identified by ELISA or RT-qPCR. The roles of miR-143-3p in Treg cell differentiation were studied via ShRNA/lentivirus transfection. Male DBA/1 J mice were separated into control, model, control mimics, and miR-143-3p mimics groups to analyze the anti-arthritis efficacy, the differentiative ability of Treg cells, and the expression level of miR-143-3p. RESULTS: Our team discovered that the Expressing level of miR-143-3p was related to RA disease activities in a negative manner, and remarkably related to antiinflammation cell factor IL-10. In vitro, the expression of miR-143-3p in the CD4+ T cells upregulated the percentage of CD4+ CD25+ Fxop3+ cells (Tregs) and forkhead box protein 3 (Foxp3) mRNA expression. Evidently, miR-143-3p mimic intervention considerably upregulated the content of Treg cells in vivo, validly avoided CIA progression, and remarkably suppressed the inflammatory events of joints in mice. CONCLUSION: Our findings indicated that miR-143-3p could ameliorate CIA through polarizing naive CD4+ T cells into Treg cells, which may be a novel strategy to treat autoimmune diseases such as RA.

Panax notoginseng saponins (PNS) attenuate Th17 cell differentiation in CIA mice via inhibition of nuclear PKM2-mediated STAT3 phosphorylation.

CONTEXT: Rheumatoid arthritis (RA) is an autoimmune disease with aberrant Th17 cell differentiation. Panax notoginseng (Burk.) F. H. Chen (Araliaceae) saponins (PNS) have an anti-inflammatory effect and can suppress Th17 cell differentiation. OBJECTIVE: To investigate mechanisms of PNS on Th17 cell differentiation in RA, and the role of pyruvate kinase M2 (PKM2). MATERIALS AND METHODS: Naive CD4+T cells were treated with IL-6, IL-23 and TGF-ß to induce Th17 cell differentiation. Apart from the Control group, other cells were treated with PNS (5, 10, 20 µg/mL). After the treatment, Th17 cell differentiation, PKM2 expression, and STAT3 phosphorylation were measured via flow cytometry, western blots, or immunofluorescence. PKM2-specific allosteric activator (Tepp-46, 50, 100, 150 µM) and inhibitor (SAICAR, 2, 4, 8 µM) were used to verify the mechanisms. A CIA mouse model was established and divided into control, model, and PNS (100 mg/kg) groups to assess an anti-arthritis effect, Th17 cell differentiation, and PKM2/STAT3 expression. RESULTS: PKM2 expression, dimerization, and nuclear accumulation were upregulated upon Th17 cell differentiation. PNS inhibited the Th17 cells, RORγt expression, IL-17A levels, PKM2 dimerization, and nuclear accumulation and Y705-STAT3 phosphorylation in Th17 cells. Using Tepp-46 (100 µM) and SAICAR (4 µM), we demonstrated that PNS (10 µg/mL) inhibited STAT3 phosphorylation and Th17 cell differentiation by suppressing nuclear PKM2 accumulation. In CIA mice, PNS attenuated CIA symptoms, reduced the number of splenic Th17 cells and nuclear PKM2/STAT3 signaling. DISCUSSION AND CONCLUSIONS: PNS inhibited Th17 cell differentiation through the inhibition of nuclear PKM2-mediated STAT3 phosphorylation. PNS may be useful for treating RA.

Modeling Approaches to Reimagine Stability (MARS) for Enabling Earlier Access to Critical Drugs for Patients with Unmet Medical Needs.

FDA's experience to date has shown that completion of stability data requirements is one of the most observed challenges for applicants of New Drug Applications (NDAs) with an expedited review designation. Since NDAs submitted under these expedited pathways often have limited available real-time stability data from the primary batches, Modeling Approaches to Reimagine Stability (MARS) have been proposed to support establishment of tentative retest periods of the drug substance and/or expiration dating period (shelf-life) of the drug product. MARS incorporate statistical principles and available tools as a part of the predictive models. In this study, a data mining exercise has been conducted with regulatory submissions of Investigational New Drug (IND) Applications, NDAs, and Abbreviated New Drug Applications (ANDAs) containing MARS data. The case studies presented herein demonstrate how MARS data has been applied to regulatory scenarios involving prediction of retest and/or shelf-life, bridging major development changes, and confirming that no degradation has been observed or predicted. Using the assumption of a linear time trend for those cases that do not display sufficient degradation to conduct MARS for projection of an expiration date, an analysis of covariance (ANCOVA) model is developed and described herein to test the hypothesis of zero slope by a p-value method. Our results show that the application of MARS adequately supported establishment of a tentative commercially viable retest date/shelf-life, thus enabling earlier access to critical drugs for patients with unmet medical needs.

Risk factors for hospital-acquired pneumonia among inpatients with mental disorders in a large mental health center within a tertiary general hospital.

BACKGROUND: Few researchers have investigated the incidence of and risk factors for hospital-acquired pneumonia (HAP) among inpatients with mental disorders in a general hospital. METHODS: This study included patients with mental disorders hospitalized in a large mental health center (situated in a general hospital) between January 1, 2017, and July 31, 2021 (excluding January 1, 2020- May 31, 2020). Risk factors for HAP were identified by logistic regression analysis after propensity score matching (PSM, 1:4) for gender, age, duration of observation, and hospital ward. RESULTS: The study included 16,864 patients. HAP incidence rate was 1.15% overall, 2.11% in closed wards, 0.75% in open wards, 4.45% in patients with organic mental disorders, 1.80% in patients with schizophrenia spectrum disorders, and 0.84% in patients with mood disorders. Risk factors for HAP after PSM were hypoproteinemia, chronic liver disease, use of clozapine, hospitalization during the previous 180 days, body mass index (BMI) ≤18.5 kg/m2, cholinesterase inhibitor use, and mood stabilizer use. CONCLUSIONS: HAP was common among inpatients with mental disorders. Risk factors for HAP in patients with mental disorders include hypoproteinemia, chronic liver disease, hospitalization during the past 180 days, BMI ≤18.5 kg/m2, and use of clozapine, cholinesterase inhibitors, or mood stabilizers.

Risk factors for community-acquired pneumonia among inpatients with mental disorders in a tertiary general hospital.

Introduction: Community-acquired pneumonia (CAP) is an important cause of hospitalization and death in patients with mental disorders. It is critical to understand the risk factors of CAP and determine prevention strategies to reduce CAP. The aim of this study is to explore the characteristics of inpatients with mental disorders who have CAP and analyze the risk factors. Methods: This retrospective study included 16,934 inpatients with mental disorders who were admitted for the first time to a tertiary general hospital between January 2017 and July 2021 (excluding January 2020-May 2020). Risk factors for CAP were identified by logistic regression analysis after propensity score matching (PSM, 1:4) for age, gender, and BMI. Results: The CAP rate of inpatients with mental disorders was 1.78%. Inpatients who had CAP had a significantly prolonged hospital stay, and were more often admitted to a closed ward or the ICU. After PSM, the multivariable analysis revealed that clozapine use (OR = 3.212, 95% CI = 1.744-5.915, P < 0.001), schizophrenia spectrum disorder (OR = 2.785, 95% CI = 1.684-4.607, P < 0.001), alcohol consumption (OR = 2.549, 95% CI = 1.586-4.096, P < 0.001), cardiovascular disease (OR = 2.299, 95% CI = 1.362-3.879, P = 0.002), Charlson comorbidity index (CCI) ≥ 3 (OR = 2.092, 95% CI = 1.342-3.260, P = 0.001), organic mental disorder (OR = 1.941, 95% CI = 1.194-3.156, P = 0.007), antipsychotic drug use (OR = 1.886, 95% CI = 1.312-2.711, P = 0.001), unmarried status (OR = 1.720, 95% CI = 1.164-2.541, P = 0.006) and junior high school education (OR = 1.591, 95%CI = 1.010-2.508, P = 0.045) were independent risk factors for CAP in inpatients with mental disorders. Conclusion: CAP was common in inpatients with mental disorders. Patients with mental disorders have unique risk factors for CAP. Further research is required to explore the relationship and mechanism between different mental disorders, antipsychotic drugs and CAP.

Triptolide inhibits Th17 differentiation via controlling PKM2-mediated glycolysis in rheumatoid arthritis.

CONTEXT: Rheumatoid arthritis (RA) is an autoimmune disease with the aberrant differentiation of T helper 17 (Th17) cells. Pyruvate kinase M2 (PKM2), a key enzyme of glycolysis, was associated with Th17 cell differentiation. AIM: To investigate the potential therapeutic effects of triptolide (TP) in collagen-induced arthritis (CIA) and Th17 cell differentiation, and elucidated the underlying mechanisms. METHODS: PKM2 expression and IL-17A production in peripheral blood of RA patients were detected by RT-qPCR or ELISA. Flow cytometry and ELISA were employed to assess the effect of Th17 cell differentiation by TP. PKM2 expression and other glycolysis-related factors were detected using RT-qPCR and Western Blot. PKM2 specific inhibitor Compound 3 K was used to verify the mechanisms. Male DBA/1J mice were divided into control, model, and TP (60 µg/kg) groups to assess the anti-arthritis effect, Th17 cell differentiation and PKM2 expression. RESULTS: PKM2 expression positively correlated with IL-17A production in RA patients. PKM2 expression was increased upon Th17 cell differentiation. Down-regulating PKM2 expression could strongly reduce Th17 cell differentiation. Molecular docking analysis predicted that TP targeted PKM2. TP treatment significantly reduced Th17 cell differentiation, PKM2 expression, pyruvate, and lactate production. In addition, compared with down-regulating PKM2 alone (Compound 3 K treatment), co-treatment with TP and Compound 3 K further significantly decreased PKM2-mediated glycolysis and Th17 cell differentiation. In CIA mice, TP repressed the PKM2-mediated glycolysis and attenuated joint inflammation. CONCLUSION: TP inhibited Th17 cell differentiation through the inhibition of PKM2-mediated glycolysis. We highlight a novel strategy for the use of TP in RA treatment.

Protection of catalpol against triptolide-induced hepatotoxicity by inhibiting excessive autophagy via the PERK-ATF4-CHOP pathway.

Catalpol significantly reduces triptolide-induced hepatotoxicity, which is closely related to autophagy. The aim of this study was to explore the unclear protective mechanism of catalpol against triptolide. The detoxification effect of catalpol on triptolide was investigated in HepaRG cell line. The detoxification effects were assessed by measuring cell viability, autophagy, and apoptosis, as well as the endoplasmic reticulum stress protein and mRNA expression levels. We found that 5-20 µg/L triptolide treatments increased the levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), and lactate dehydrogenase (LDH), as well as the expression of autophagy proteins including LC3 and Beclin1. The expression of P62 was downregulated and the production of autophagosomes was increased, as determined by transmission electron microscope and monodansylcadaverine staining. In contrast, 40 µg/L catalpol reversed these triptolide-induced changes in the liver function index, autophagy level, and apoptotic protein expression, including Cleaved-caspase3 and Cleaved-caspase9 by inhibiting excessive autophagy. Simultaneously, catalpol reversed endoplasmic reticulum stress, including the expression of PERK, which regulates autophagy. Moreover, we used the PERK inhibitor GSK2656157 to prove that the PERK-ATF4-CHOP pathway of the unfolded protein response is an important pathway that could induce autophagy. Catalpol inhibited excessive autophagy by suppressing the PERK pathway. Altogether, catalpol protects against triptolide-induced hepatotoxicity by inhibiting excessive autophagy via the PERK-ATF4-CHOP pathway. The results of this study are beneficial to clarify the detoxification mechanism of catalpol against triptolide-induced hepatotoxicity and to promote the application of triptolide.

Catalpol Inhibits Tregs-to-Th17 Cell Transdifferentiation by Up-Regulating Let-7g-5p to Reduce STAT3 Protein Levels.

PURPOSE: Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease, and Th17 cells are key factors in the pathogenesis of human inflammatory conditions, such as RA. Catalpol (CAT), a component in Rehmanniae Radix (RR), has been found to regulate human immunity. However, the effects of CAT on Th17 cell differentiation and improvement of RA are not clear. MATERIALS AND METHODS: Collagen-induced arthritis (CIA) mice were constructed to detect the effects of CAT on arthritis and Th17 cells. The effect of CAT on Th17 differentiation was evaluated with let-7g-5p transfection experiments. Flow cytometry was used to detect the proportion of Th17 cells after CAT treatment. Levels of interleukin-17 and RORγt were assessed by qRT-PCR and enzyme-linked immunosorbent assay. The expression of signal transducer and activator of transcription 3 (STAT3) was determined by qRT-PCR and Western blot. RESULTS: We found that the proportion of Th17 cells was negatively associated with let-7g-5p expression in CIA mice. In in vitro experiments, CAT suppressed traditional differentiation of Th17 cells. Simultaneously, CAT significantly decreased Tregs-to-Th17 cells transdifferentiation. Our results demonstrated that CAT inhibited Tregs-to-Th17 cells transdifferentiation by up-regulating let-7g-5p and that the suppressive effect of CAT on traditional differentiation of Th17 cells is not related with let-7-5p. CONCLUSION: Our data indicate that CAT may be a potential modulator of Tregs-to-Th17 cells transdifferentiation by up-regulating let-7g-5p to reduce the expression of STAT3. These results provide new directions for research into RA treatment.

miR-143-3p Inhibits the Differentiation of Osteoclast Induced by Synovial Fibroblast and Monocyte Coculture in Adjuvant-Induced Arthritic Rats.

Osteoclast, which mediates overactive bone resorption, is one of the key factors for bone destruction in rheumatoid arthritis (RA). Existing studies have shown that abnormal miR-143-3p expression was observed in both RA patients and arthritis animals, which can participate in osteoclast differentiation, and mitogen-activated protein kinase (MAPK) signaling pathway was closely related to osteoclast differentiation. The primary objective of the current study was to determine the role of miR-143-3p in the progression of osteoclast differentiation and its relationship with MAPK signaling pathways. The results showed that miR-143-3p inhibited osteoclast differentiation and decreased the levels of M-CSF and RANKL during osteoclast differentiation. miR-143-3p inhibited the expression of MAPK signaling proteins, which is ERK1/2 in the early stage and JNK in the later stage of osteoclast differentiation. It was also observed that MAPK inhibitors upregulated miR-143-3p expression in osteoclast differentiation. Taken together, our results suggested that miR-143-3p could inhibit the differentiation of osteoclast, which was related to inhibiting MAPK signaling pathways. This may provide a novel strategy for curing RA.

MicroRNA-26b-5p alleviates murine collagen-induced arthritis by modulating Th17 cell plasticity.

Rheumatoid arthritis (RA) is a chronic autoimmune disease, and the abnormal differentiation of IL-17-producing T helper (Th17) cells is an important factor in the pathogenesis. Previous studies have shown that microRNAs (miRNAs, miR) act as key regulators of Th17 cells. However, the effects of miRNAs on Th17 cell differentiation and plasticity in RA are not clear. In this study, not only low miR-26b-5p expression and high IL-17A level were observed in the peripheral blood of RA patients, but also the negative correlation between miR-26b-5p and IL-17A was explored. The changes in collagen-induced arthritis (CIA) mice were consistent with those in RA patients. The results of in vitro experiments showed that miR-26b-5p mainly inhibited the initial differentiation of Th17 cells but did not impact the differentiation of induced-Treg into Th17-like cells. Meanwhile, miR-26b-5p mimics treatment alleviated inflammatory responses and reduced Th17 proportion in CIA mice. These results indicated that miR-26b-5p could alleviate the development of mice CIA by inhibiting the excessive Th17 cells, and that miR-26b-5p could modulate the plasticity of Th17 cell differentiation in RA, mainly block the initial differentiation. This may provide a novel strategy for the clinical treatment of RA.

Statistical methods of screening cut point determination in immunogenicity studies.

Background: Currently, screening cut point (CP) calculated from an assay validation with replicates are applied to an immunogenicity study with nonreplicates, for which the antidrug antibodies rate is determined. IID treats the replicate of a sample as coming from another independent sample. AVE uses average results from each sample across runs but inter-assay variability is reduced. Therefore, we propose a random effect model (REM) for calculating CP. Materials & method: We investigate impact of noncompatibility design between validation and immunogenicity studies on CP and compare these methods. Conclusion: IID may not fit for use when replicates' variability dominates all sources of uncertainty. REM considers covariance structure of repeated measurements. CP by REM is smaller than that by IID but larger than that by AVE.

Statistical Considerations in Assessing In Vivo Adhesion with Transdermal and Topical Delivery Systems for New Drug Applications.

Proper adhesion plays a critical role in maintaining a consistent, efficacious, and safe drug delivery profile for transdermal and topical delivery systems (TDS). As such, in vivo skin adhesion studies are recommended by regulatory agencies to support the approval of TDS in new drug applications (NDAs). A draft guidance for industry by the US Food and Drug Administration outlines a non-inferiority comparison between a test product and its reference product for generic TDS in abbreviated new drug applications (ANDAs). However, the statistical method is not applicable for evaluating adhesion of TDS for NDAs, because no reference product exists. In this article, we explore an alternative primary endpoint and a one-sided binomial test to evaluate in vivo adhesion of TDS in NDAs. Statistical considerations related to the proposed approach are discussed. To understand its potential use, the proposed approach is applied to data sets of in vivo adhesion studies from selected NDAs and ANDAs.

Correction to: Equivalence Testing of Complex Particle Size Distribution Profiles Based on Earth Mover's Distance.

On page 5, in the second paragraph, the authors inadvertently included inaccurate information for the description of the analytical method.

The ELISA Detectability and Potency of Pegfilgrastim Decrease in Physiological Conditions: Key Roles for Aggregation and Individual Variability.

PEGylated recombinant human granulocyte colony stimulating factor (pegfilgrastim) is used clinically to accelerate immune reconstitution following chemotherapy and is being pursued for biosimilar development. One challenge to overcome in pegfilgrastim biosimilar development is establishing pharmacokinetic (PK) similarity, which is partly due to the degree of PK variability. We herein report that commercially available G-CSF and PEG ELISA detection kits have different capacities to detect pegfilgrastim aggregates that rapidly form in vitro in physiological conditions. These aggregates can be observed using SDS-PAGE, size-exclusion chromatography, dynamic light scattering, and real-time NMR analysis and are associated with decreased bioactivity as reflected by reduced drug-induced cellular proliferation and STAT3 phosphorylation. Furthermore, individual variability in the stability and detectability of pegfilgrastim in human sera is also observed. Pegfilgrastim levels display marked subject variability in sera from healthy donors incubated at 37 °C. The stability patterns of pegfilgrastim closely match the stability patterns of filgrastim, consistent with a key role for pegfilgrastim's G-CSF moiety in driving formation of inactive aggregates. Taken together, our results indicate that individual variability and ELISA specificity for inactive aggregates are key factors to consider when designing and interpreting studies involving the measurement of serum pegfilgrastim concentrations.

MicroRNA let-7g-5p alleviates murine collagen-induced arthritis by inhibiting Th17 cell differentiation.

Rheumatoid arthritis (RA) is a chronic and systemic autoimmune disease with complicated pathogenesis. IL-17-producing T helper cells (Th17) are important players in the RA process. Despite numerous researches have proven that microRNAs (miRNAs) are crucial to regulate autoimmune diseases including RA, the effect of miRNAs on Th17 cell differentiation and function in the RA progress is not clear. Here, our results showed that the expression of miRNA let-7g-5p was substantially lower in RA patients and CIA mice compared with healthy controls, accompanied by the increased Th17 cell population. Furthermore, the inhibition of let-7g-5p on Th17 cell differentiation and function were verified in vitro. Notably, the disease severity in CIA mice was significantly alleviated after the treatment of let-7g-5p mimics. In addition, let-7g-5p mimics treatment markedly down-regulated the frequency of Th17 cells in CIA mice. Taken together, our findings indicate that let-7g-5p can ameliorate CIA through blocking the differentiation of Th17 cells, which may be a novel strategy to treat autoimmune diseases such as RA.

Non-inferiority tests for binary endpoints with variable margins.

Non-inferiority comparison between binary response rates of test and reference treatments is often performed in clinical studies. The most common approach to assess non-inferiority is to compare the difference between the estimated response rates with some margin. Previous methods use a variety of margins, including fixed margin, step-wise constant margin, and piece-wise smooth margin, where the latter two are functions of the reference response rate. The fixed margin approach assumes that the margin can be determined from historical trials with the consistent difference between the reference treatment and placebo, which may not be available. The step-wise constant margin approach suffers discontinuity in the power function which can cause trouble in sample size determination. Furthermore, many methods ignore the variability in margins dependent on the estimated reference response rate, leading to poor type I error control and power function approximation. In this study, we propose a variable margin approach to overcome the difficulties in fixed and step-wise constant margin approaches. We discuss several test statistics and evaluate their performance through simulation studies.

A modified Wald test for reference scaled assessment of analytical equivalence.

For the reference scaled equivalence hypothesis to reduce the deficiency of the current practice in analytical equivalence assessment, the Wald test with Constrained Maximum Likelihood Estimate (CMLE) of the standard error was proposed to improve the efficiency when the sample sizes of test and reference product lots are small, and variances are unequal. However, by using the Wald test with CMLE standard error, simulations show that the type I error rate is below the nominal significance level. We proposed the Modified Wald test with CMLE standard error by replacing the maximum likelihood estimate of reference standard deviation with the sample estimate (MWCMLE), resulting in further improvement of type I error rate and power over the Wald test with CMLE standard error. In this paper, we further compare the proposed MWCMLE method to the Exact-test-Based (EB) method and the Generalized Pivotal Quantity (GPQ) method with equal or unequal variances, or equal or unequal sample sizes of both product lots. The simulations show that the proposed MWCMLE method outperforms the other two methods in type I error rate control and power improvement.

Equivalence Testing of Complex Particle Size Distribution Profiles Based on Earth Mover's Distance.

Particle size distribution (PSD) is an important property of particulates in drug products. In the evaluation of generic drug products formulated as suspensions, emulsions, and liposomes, the PSD comparisons between a test product and the branded product can provide useful information regarding in vitro and in vivo performance. Historically, the FDA has recommended the population bioequivalence (PBE) statistical approach to compare the PSD descriptors D50 and SPAN from test and reference products to support product equivalence. In this study, the earth mover's distance (EMD) is proposed as a new metric for comparing PSD particularly when the PSD profile exhibits complex distribution (e.g., multiple peaks) that is not accurately described by the D50 and SPAN descriptor. EMD is a statistical metric that measures the discrepancy (distance) between size distribution profiles without a prior assumption of the distribution. PBE is then adopted to perform statistical test to establish equivalence based on the calculated EMD distances. Simulations show that proposed EMD-based approach is effective in comparing test and reference profiles for equivalence testing and is superior compared to commonly used distance measures, e.g., Euclidean and Kolmogorov-Smirnov distances. The proposed approach was demonstrated by evaluating equivalence of cyclosporine ophthalmic emulsion PSDs that were manufactured under different conditions. Our results show that proposed approach can effectively pass an equivalent product (e.g., reference product against itself) and reject an inequivalent product (e.g., reference product against negative control), thus suggesting its usefulness in supporting bioequivalence determination of a test product to the reference product which both possess multimodal PSDs.