Stages Of Drug Development Research Articles

Replacement in angiogenesis research: Studying mechanisms of blood vessel development by animal-free in vitro, in vivo and in silico approaches.

Angiogenesis, the development of new blood vessels from pre-existing ones, is an essential process determining numerous physiological and pathological conditions. Accordingly, there is a high demand for research approaches allowing the investigation of angiogenic mechanisms and the assessment of pro- and anti-angiogenic therapeutics. The present review provides a selective overview and critical discussion of such approaches, which, in line with the 3R principle, all share the common feature that they are not based on animal experiments. They include in vitro assays to study the viability, proliferation, migration, tube formation and sprouting activity of endothelial cells in two- and three-dimensional environments, the degradation of extracellular matrix compounds as well as the impact of hemodynamic forces on blood vessel formation. These assays can be complemented by in vivo analyses of microvascular network formation in the chorioallantoic membrane assay and early stages of zebrafish larvae. In addition, the combination of experimental data and physical laws enables the mathematical modeling of tissue-specific vascularization, blood flow patterns, interstitial fluid flow as well as oxygen, nutrient and drug distribution. All these animal-free approaches markedly contribute to an improved understanding of fundamental biological mechanisms underlying angiogenesis. Hence, they do not only represent essential tools in basic science but also in early stages of drug development. Moreover, their advancement bears the great potential to analyze angiogenesis in all its complexity and, thus, to make animal experiments superfluous in the future.

The Relevance of Crystal Forms in the Pharmaceutical Field: Sword of Damocles or Innovation Tools?

This review is aimed to provide to an “educated but non-expert” readership and an overview of the scientific, commercial, and ethical importance of investigating the crystalline forms (polymorphs, hydrates, and co-crystals) of active pharmaceutical ingredients (API). The existence of multiple crystal forms of an API is relevant not only for the selection of the best solid material to carry through the various stages of drug development, including the choice of dosage and of excipients suitable for drug development and marketing, but also in terms of intellectual property protection and/or extension. This is because the physico-chemical properties, such as solubility, dissolution rate, thermal stability, processability, etc., of the solid API may depend, sometimes dramatically, on the crystal form, with important implications on the drug’s ultimate efficacy. This review will recount how the scientific community and the pharmaceutical industry learned from the catastrophic consequences of the appearance of new, more stable, and unsuspected crystal forms. The relevant aspects of hydrates, the most common pharmaceutical solid solvates, and of co-crystals, the association of two or more solid components in the same crystalline materials, will also be discussed. Examples will be provided of how to tackle multiple crystal forms with screening protocols and theoretical approaches, and ultimately how to turn into discovery and innovation the purposed preparation of new crystalline forms of an API.

Spray drying and nano spray drying as manufacturing methods of drug-loaded polymeric particles.

In this review, benefits and drawbacks of the process of spray drying and nano spray drying with regard to the manufacturing of polymeric particles for pharmaceutical applications are discussed. Spray drying has been used for many years in the food, chemical and pharmaceutical industries for converting liquids into solids, in order to form products of uniform appearance. The construction of spray dryer enables to atomize the liquid into small droplets, which ensures a large surface area for heat and mass transfer, and significantly shortens the processing. Each droplet dries to an individual solid microparticle of characteristic features that can be tailored by optimizing formulation variables and critical process parameters. Since spray drying technology is easy to scale up and can be used for drying almost any drug in a solution or suspension, there are numerous examples of products in clinical use, in which this process has been successfully applied to improve drug stability, enhance bioavailability or control its release rate. In recent years, nano spray drying technology has been proposed as a method for lab-scale manufacturing of nanoparticles. Such an approach is of particular interest at early stages of drug development, when a small amount of new chemical entities is available. Here, the nebulization technique is used for feed atomization, while laminar gas flow in the drying chamber ensures gentle drying conditions. Moreover, electrostatic collectors have gradually replaced cyclone separators, ensuring high effectiveness in producing solid nanoparticles, even if a small volume of the sample is processed.

Current practices for QSP model assessment: an IQ consortium survey.

Quantitative Systems Pharmacology (QSP) modeling is increasingly applied in the pharmaceutical industry to influence decision making across a wide range of stages from early discovery to clinical development to post-marketing activities. Development of standards for how these models are constructed, assessed, and communicated is of active interest to the modeling community and regulators but is complicated by the wide variability in the structures and intended uses of the underlying models and the diverse expertise of QSP modelers. With this in mind, the IQ Consortium conducted a survey across the pharmaceutical/biotech industry to understand current practices for QSP modeling. This article presents the survey results and provides insights into current practices and methods used by QSP practitioners based on model type and the intended use at various stages of drug development. The survey also highlights key areas for future development including better integration with statistical methods, standardization of approaches towards virtual populations, and increased use of QSP models for late-stage clinical development and regulatory submissions.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10928-022-09811-1.

Matching within a hybrid RCT/RWD: framework on associated causal estimands

ABSTRACT As the regulatory environment becomes progressively receptive toward utilizing real-world evidence, a spectrum of real-world data incorporation techniques in trial conduct and analysis has seen increasing interest and adoption in different stages of drug development. Of particular interest is leveraging external control data to augment the control arm in a concurrent randomized controlled trial, where patients are enrolled in both investigational treatment arm and the control arm. Yet despite the emerging literature in external data borrowing in a hybrid trial setting, very little discussion focuses on delineating what should be matched and what is actually being estimated, especially when a variety of matching schemes can be considered. In general, external control can be matched in four different ways: (1) matching with the intersection between investigational treatment and concurrent control, (2) matching with the union of concurrent investigational treatment and concurrent control, (3) matching with concurrent control alone, and (4) matching with investigational treatment alone. In this article, the formulation of estimands for different matching schemes are detailed to describe what these matching methods facilitate to answer. Simulation studies are also conducted to evaluate the performance characteristics under different matching schemes, estimation methods, effect size assumptions, and missingness of confounders.

The Efficacy and Safety of Cystic Fibrosis Gene Therapy Clinical Trials: A Systematic Review and Meta-Analysis

BackgroundGene therapy has been proposed as a treatment approach for cystic fibrosis by replacing the single defective gene, cystic fibrosis transmembrane regulator (CFTR), through topical lung delivery. Relatively few studies have addressed gene therapy for cystic fibrosis.Objectives Via referral to the published literature, this study aimed to identify any success of the gene therapy approach for cystic fibrosis regarding experimental and routine clinical outcomes in different drug development stages, and to determine any adverse effects noted. MethodologyA search of the PubMed database (NCBI) for 1989–2020 was made using predefined selection criteria for clinical trials on patients with cystic fibrosis receiving viral and non-viral lung delivery systems of the CFTR gene. Several features in the reviewed studies were examined, including clinical phase (1–3), sample size, delivery target cells/vector, and reported adverse effects. A quantitative estimate of treatment intervention success was evaluated using a meta-analysis approach.Results A total of 20 studies with 549 patients were included in the review. The studies involved the delivery of the defective gene to the lung, nasal mucosa, and sinuses, and were mainly phase 1–2, randomized controlled trials; there were no phase three studies. The vector for gene transfer was liposome or viral. % predicted FEV1 was statistically significant between intervention and control patients in two trials. Gene transfer was detected to a higher degree in intervention patients than control; this outcome measure was assessed using bronchoscopy assessment of vector-specific DNA and mRNA expression in lung and nasal mucosa. These effects, however, were temporary. The safety of the gene therapy approach was confirmed. ConclusionReportedly, the gene therapy approach is safe but has limited and temporary efficacy. Newer approaches should thus be engineered to deliver the necessary genetic material with the desired, full-scale efficacy.

CSatDTA: Prediction of Drug-Target Binding Affinity Using Convolution Model with Self-Attention.

Drug discovery, which aids to identify potential novel treatments, entails a broad range of fields of science, including chemistry, pharmacology, and biology. In the early stages of drug development, predicting drug–target affinity is crucial. The proposed model, the prediction of drug–target affinity using a convolution model with self-attention (CSatDTA), applies convolution-based self-attention mechanisms to the molecular drug and target sequences to predict drug–target affinity (DTA) effectively, unlike previous convolution methods, which exhibit significant limitations related to this aspect. The convolutional neural network (CNN) only works on a particular region of information, excluding comprehensive details. Self-attention, on the other hand, is a relatively recent technique for capturing long-range interactions that has been used primarily in sequence modeling tasks. The results of comparative experiments show that CSatDTA surpasses previous sequence-based or other approaches and has outstanding retention abilities.

Pharmacokinetic/Pharmacodynamic Modeling and Application in Antibacterial and Antifungal Pharmacotherapy: A Narrative Review.

Pharmacokinetics and pharmacodynamics are areas in pharmacology related to different themes in the pharmaceutical sciences, including therapeutic drug monitoring and different stages of drug development. Although the knowledge of these disciplines is essential, they have historically been treated separately. While pharmacokinetics was limited to describing the time course of plasma concentrations after administering a drug-dose, pharmacodynamics describes the intensity of the response to these concentrations. In the last decades, the concept of pharmacokinetic/pharmacodynamic modeling (PK/PD) emerged, which seeks to establish mathematical models to describe the complete time course of the dose-response relationship. The integration of these two fields has had applications in optimizing dose regimens in treating antibacterial and antifungals. The anti-infective PK/PD models predict the relationship between different dosing regimens and their pharmacological activity. The reviewed studies show that PK/PD modeling is an essential and efficient tool for a better understanding of the pharmacological activity of antibacterial and antifungal agents.

Characteristics of histamine H4 receptor agonist-induced allergic conjunctivitis model in Guinea pigs

Histamine is strongly associated with the onset of allergic conjunctivitis. The most recent cloned histamine H4 receptor antagonist is highly expected as a new therapeutic drug candidate. As a model for a therapeutic drug targeting the histamine H4 receptor, a mouse model in which conjunctivitis symptoms are induced by instilling 4-methylhistamine, a histamine H4 receptor agonist, has been reported. However, the affinity of the H4 receptor for histamine varies in species, and it is known that the histamine binding affinity for the guinea pig H4 receptor is closer to that for human receptor than mice receptor. In this paper, we investigated a possibility that a guinea pig model would become a drug efficacy evaluation model with higher evaluation accuracy than the mouse model.As a result, hyperemia was observed in the conjunctivae and iris of guinea pigs after instillation of 4-methylhistamine and specifically suppressed by the histamine H4 receptor antagonist. Unlikely to the previously reported mouse model, however, none of edema, increased vascular permeability or scratching behavior was observed, suggesting that there may be differences between mice and guinea pigs not only in the binding affinity of histamine to the H4 receptor but also in the biological reaction to 4-methylhistamine. Although the symptoms of allergic conjunctivitis do not appear comprehensively in the guinea pig model, results of this study indicated a possibility that this model can be used as a simple screening model in the early stages of drug development.

DESIGN-EXPERT SOFTWARE (DOE): AN APPLICATION TOOL FOR OPTIMIZATION IN PHARMACEUTICAL PREPARATIONS FORMULATION

Formulation is a crucial stage in drug development since it determines the best formula. The quality of the preparation is good and fulfills the standard parameters when using the best formula. This stage is completed through laboratory experiments that take a long time to complete. To address this, software utilizing computer technology, such as software Design Expert, can be used. The goal of this investigation is to see how Design Expert is used in research formulation and optimization. The method of writing a review was carried out by searching Google Scholar and Science Direct with the keywords "Formulation" and "Design Expert," yielding 63 articles, which were then screened using inclusion criteria, notably field of research on formulation optimization accepted for publication between 2011 and April 2020, and exclusion in the form of review articles. The review's findings suggest that the platform is widely utilized and effective at reducing the number of trials, time, and costs associated with formulation development.

Non-clinical considerations for supporting accelerated inclusion of pregnant women in pre-licensure clinical trials with anti-HIV agents.

IntroductionTo allow the continued participation of women enrolled in pre‐licensure clinical trials who become pregnant, and to potentially enrol pregnant women in clinical trials, non‐clinical developmental and reproductive toxicology studies (DART) are essential. Generally during pharmaceutical development, DART studies are conducted late during clinical development, leading to the exclusion of pregnant women from enrolment and withdrawal of women becoming pregnant during pre‐licensure trials.DiscussionCompleting all DART studies prior to or early during the conduct of phase 3 trials (i.e. earlier than current common practice) can accelerate and facilitate the inclusion of women who become pregnant during pre‐licensure trials to remain on study drug and to potentially enrol pregnant women more rapidly. Promoting complementary strategies, such as alternative combinations of DART study designs and physiologically based pharmacokinetic modelling, could better inform drug dosing and safety in pregnancy at an earlier stage in drug development. The interpretation of the results of non‐clinical DART studies is often complex. Institutional review boards/ethics committees should have access to relevant expertise for interpretation and application of results of non‐clinical developmental and reproductive toxicity studies. Clear communication and thorough understanding of non‐clinical findings and the overall benefit–risk profile of the product are critical to review protocols and determine if women who become pregnant during a clinical trial could continue on study drug and/or to enrol pregnant women in the trial. The informed consent document should be well written so that participants can make an informed decision to stay on study drug or participate in a trial during pregnancy. Ultimately, the decision to allow women who become pregnant during pre‐licensure trials to remain on study will depend on the totality of the evidence and benefit–risk considerations.ConclusionsWe propose that industry completes non‐clinical reproductive toxicity studies prior to or early during the conduct of phase 3 trials in HIV drug development, especially for priority agents, and potentially uses alternative DART study design strategies to achieve this goal.

Comparison of assay formats used for the detection of pre-existing anti-drug antibodies against monoclonal antibodies.

Aim: Assessment of pre-existing anti-drug antibody (preADA) reactivity at early drug development stages can be beneficial for candidate selection. We investigated the applicability of a generic immune-complex anti-drug antibody (ADA) assay for early preADA assessment as an easily available alternative to the commonly used ADA bridging assay. Results: The results confirmed the expected assay difference regarding isotype detectability. Tested drug candidates were identified as preADA-reactive using the immune-complex ADA assay despite its limitation of not being able to detect IgM-type preADAs. Conclusion: We recommend a purpose-driven use of the two assay formats. For the purpose of ranking different Pro329Gly mutation-bearing drug candidates, the immune-complex ADA assay is preferred in the phase before selecting a drug for clinical development.

Alternative funding models for medical innovation: the role of product development partnerships in product innovation for infectious diseases

ABSTRACT Over the past years, there has been an increasing trend in the number of product development partnerships (PDPs), primarily seeking to discover and produce new products in response to the global health threat posed by infectious diseases. This research exploits public and subscription-based databases to examine PDPs’ attributes and their impact on medical innovation in infectious diseases. We find that i) non-private funding is beneficial in the early stages of drug development by PDPs, ii) specific funder and product types are essential for the success of products developed by PDPs, iii) public sector funding is more common in products with lower chances of being approved, and iv) the lower the scientific advances in a sub-disease area are, the lower the likelihood of a product in that area of succeeding.

The Future of Seed Amplification Assays and Clinical Trials.

Prion-like seeded misfolding of host proteins is the leading hypothesised cause of neurodegenerative diseases. The exploitation of the mechanism in the protein misfolding cyclic amplification (PMCA) and real-time quaking-induced conversion (RT-QuIC) assays have transformed prion disease research and diagnosis and have steadily become more widely used for research into other neurodegenerative disorders. Clinical trials in adult neurodegenerative diseases have been expensive, slow, and disappointing in terms of clinical benefits. There are various possible factors contributing to the failure to identify disease-modifying treatments for adult neurodegenerative diseases, some of which include: limited accuracy of antemortem clinical diagnosis resulting in the inclusion of patients with the “incorrect” pathology for the therapeutic; the role of co-pathologies in neurodegeneration rendering treatments targeting one pathology alone ineffective; treatment of the primary neurodegenerative process too late, after irreversible secondary processes of neurodegeneration have become established or neuronal loss is already extensive; and preclinical models used to develop treatments not accurately representing human disease. The use of seed amplification assays in clinical trials offers an opportunity to tackle these problems by sensitively detecting in vivo the proteopathic seeds thought to be central to the biology of neurodegenerative diseases, enabling improved diagnostic accuracy of the main pathology and co-pathologies, and very early intervention, particularly in patients at risk of monogenic forms of neurodegeneration. The possibility of quantifying proteopathic seed load, and its reduction by treatments, is an attractive pharmacodynamic biomarker in the preclinical and early clinical stages of drug development. Here we review some potential applications of seed amplification assays in clinical trials.

Landscape Analysis of the Application of Artificial Intelligence and Machine Learning in Regulatory Submissions for Drug Development From 2016 to 2021.

Landscape Analysis of the Application of Artificial Intelligence and Machine Learning in Regulatory Submissions for Drug Development From 2016 to 2021.

Abstract 4093: COSMIC Actionability: Supporting precision oncology through Identification of actionable mutations from clinical trials databases and publications

Abstract The availability of drugs that are effective in cancer patients with specific somatic mutations is rapidly evolving. Finding the most recent information is not straightforward; clinical progress and drug approvals are recorded in clinical trial repositories, files from drug regulatory agencies, publications and conference abstracts. Often there is a delay between trials reaching their outcomes, publication and deposition of results in clinical trial databases. COSMIC Actionability is a new addition to COSMIC’s (Catalogue Of Somatic Mutations In Cancer) portfolio of navigational databases for precision oncology. It indicates the availability of drugs that target mutations and tracks the progress of novel drugs through clinical development. All stages of drug development are represented, through safety and clinical efficacy to market approval, with additional data from case studies expanding mutation coverage. For each mutation-cancer type combination, a simple tiered system indicates whether marketed drugs are available and if not, indicates the progress of drug development efforts. Trial records available in databases such as Clinical Trials.gov and EudraCT are supplemented with trials identified in publications. Trial progression and outcomes are recorded; details are sourced from clinical trial databases, publications, conference abstracts, corporate announcements and regulatory authorities such as the FDA. Curation identifies results for approximately 40% more trials than are available in clinical trial databases alone. Like other COSMIC resources, Actionability is manually curated by Ph.D. level experts. The current version of COSMIC Actionability (October 2021) has 49 fully curated genes with a further 237 having some clinical information. Details of 6244 drug-cancer type combinations are available, of which 2224 have clinical results. 963 drugs are represented, in 2224 treatment combinations. 149 point mutations and 520 further mutations or fusions are represented. This dataset will be made freely available in 2022 then released quarterly, with extended gene coverage and updates of previous content. Citation Format: Steven C. Jupe, Nidhi Bindal, Zbyslaw Sondka, Shicai Wang, Sumodh Nair, Laura Ponting, Doron Sondheimer, Charlie Hathaway, Simon A. Forbes. COSMIC Actionability: Supporting precision oncology through Identification of actionable mutations from clinical trials databases and publications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4093.

Selection of the candidate compound at an early stage of new drug development: retrospective pharmacokinetic and metabolic evaluations of valsartan using common marmosets

Valsartan is an antihypertensive drug that was developed using common marmosets (Callithrix jacchus) in pivotal toxicity studies as a non-rodent species. The aim of the present study was to investigate the utility of marmosets in the candidate selection of this drug from a pharmacokinetic and metabolic viewpoint. Valsartan, as well as three other angiotensin II type-I receptor blockers, assumed as competitive candidates, were administered to common marmosets. Human pharmacokinetic parameters predicted by single-species allometric scaling and Wajima superposition suggested that valsartan may exhibit promising pharmacokinetic properties in humans. In vitro metabolic studies of valsartan using isolated rat, dog, marmoset, cynomolgus monkey, and human hepatocytes revealed that the marmoset was the most relevant animal species to humans presenting with the most abundant human metabolite, 4-hydroxyvalsartan. Oral administration of an elevated dose of valsartan to a common marmoset demonstrated that the level of 4-hydroxyvalsartan in the plasma was comparable to that in clinical practice and suggested that safety of the human metabolite might have been confirmed in the toxicity studies using common marmosets. These results suggest that common marmosets, the small, non-human primates, had been a suitable species for the development of valsartan.

Impact of Sr2+ and hypoxia on 3D triple cultures of primary human osteoblasts, osteocytes and osteoclasts

An in vitro bone triple culture involving human primary osteoblasts, osteocytes and osteoclasts enables the investigation of bone healing factors, drugs or biomaterials in a model system for native bone tissue. The present study analyses the impact of Sr2+ as well as hypoxic cultivation (5% O2 content or chemically induced by Co2+) on bone cells. The three cell types were cultivated together in the presence of 100 µM Sr2+, hypoxic conditions or in the presence of 75 µM Co2+. After cultivation the cell types were separated and analysed on mRNA and protein level individually. In response to Sr2+ osteoblasts showed a downregulation of IBSP expression and a stimulation of ALP activity. Osteocyte gene marker expression of PDPN, MEPE, RANKL, OPG, osteocalcin and likewise the amount of secreted osteocalcin was reduced in the presence of Sr2+. Activity of osteoclast-specific enzymes TRAP and CAII was enhanced compared to the Sr2+ free control. Hypoxic conditions induced by both 5% O2 or a Co2+ treatment led to decreased DNA content of all bone cells and downregulated expression of osteoblast markers ALPL and IBSP as well as osteocyte markers PDPN, RANKL and OPG. In addition, Co2+ induced hypoxia decreased gene and protein expression of osteocalcin in osteocytes. In response to the Co2+ treatment, the TRAP gene expression and activity was increased. This study is the first to analyse the effects of Sr2+ or hypoxia on triple cultures with primary human bone cells. The investigated in vitro bone model might be suitable to reduce animal experiments in early stages of biomaterial and drug development.

Lesion-specific radiomics analysis shows promising results for early-stage efficacy assessment of IOA-244 in uveal melanoma.

3068 Background: Radiomics is an image based approach that allows for characterization and quantification of tumor lesions in cancer patients. Radiomics has been proven capable of potentially adding value in the diagnostic and prognostic patient managment. In this study we evaluated the potential of Radiomics to bring additional insight also in early drug development. Methods: All the visible malignant lung and liver metastasis lesions of 7 uveal melanoma patients (86% of women, 60±11y) treated with IOA-244 (EudraCT 2019-000686-20) were manually segmented and analyzed in their size and shape via a radiomics approach. The CT scans at baseline and first follow-up (8 weeks) were included in the study and compared. Descriptive statistics and linear mixed effect (LME) models were used to quantify volumetric lesion-specific response to treatment. Response has been defined both as continuous variable and in three discrete categories (lesion shrinkage, stable and progressive disease for a volume change of [-100%;-0%];[0%-+25%] and > 25%, respectively). The influence of lesion shape at baseline (e.g. compactness, elongation or surface roughness among others) on the treatment response has been explore through LME models as well. Results: We identified and segmented 126 metastatic lesions (70 lung and 56 liver) from baseline scans and 122 lesions (71 lung and 51 liver) from post treatment scans. Of those, 64% could be consistently mapped between visits, resulting in a total of 147 matching lesions on which the radiomics analysis was performed. We found 19% of complete response and 16% of new lesions appearing. 8 weeks after treatment start, we observed non progressive disease in 61% of all lesions, of which 42% was shrinking. LME did not show a significant change in lesion volume between visits, but the mean difference between visits was negative. LME did show that lesion shape is significantly different between progressors and non-progressors at baseline for lung lesions (compact and irregular lesions are more likely to respond), and that there are moderate correlations (0.4-0.7) between tumor shape and volume change for liver lesions (compact lesions have a larger volume drop). Conclusions: This work demonstrates both the clinical potential of IOA-244 for treatment of Uveal Melanoma patients with lesions in the lung and in the liver and the potential of radiomics individual lesion analysis for clinical research in the very early stages of drug development. Lesion evolution volumetric assessment has allowed a more accurate and sensitive understanding of IOA-244 efficacy and impact across different lesions, in both lung and liver. Radiomics showed a promising response of selected population to IOA-244 over the first time point (W0-W8). A further radiomics analysis on next follow-up scans would allow a radiological proof of treatment-induced changes and long-term patient outcome prediction.

An efficient and scalable data analysis solution for automated electrophysiology platforms.

Ion channels are drug targets for neurologic, cardiac, and immunologic diseases. Many disease-associated mutations and drugs modulate voltage-gated ion channel activation and inactivation, suggesting that characterizing state-dependent effects of test compounds at an early stage of drug development can be of great benefit. Historically, the effects of compounds on ion channel biophysical properties and voltage-dependent activation/inactivation could only be assessed by using low-throughput, manual patch clamp recording techniques. In recent years, automated patch clamp (APC) platforms have drastically increased in throughput. In contrast to their broad utilization in compound screening, APC platforms have rarely been used for mechanism of action studies, in large part due to the lack of sophisticated, scalable analysis methods for processing the large amount of data generated by APC platforms. In the current study, we developed a highly efficient and scalable software workflow to overcome this challenge. This method, to our knowledge the first of its kind, enables automated curve fitting and complex analysis of compound effects. Using voltage-gated sodium channels as an example, we were able to immediately assess the effects of test compounds on a spectrum of biophysical properties, including peak current, voltage-dependent steady state activation/inactivation, and time constants of activation and fast inactivation. Overall, this automated data analysis method provides a novel solution for in-depth analysis of large-scale APC data, and thus will significantly impact ion channel research and drug discovery.