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The US Food and Drug Administration (FDA) has taken steps to bring efficiency to the development of biosimilars, including establishing guidance for the use of pharmacokinetic and pharmacodynamic (PD) similarity study data without a comparative clinical study with efficacy end point(s). To better understand the potential role for PD biomarkers in biosimilar development and inform best practices for biomarker selection and analysis, we conducted a randomized, double‐blinded, placebo‐controlled, single‐dose, parallel‐arm clinical study in healthy participants. Eighty‐four healthy participants (n = 12 per dose arm) received either placebo or one of three doses of either interferon β‐1a (7.5–30 μg) or pegylated interferon β‐1a (31.25–125 μg) to evaluate the maximum change from baseline and the baseline‐adjusted area under the effect curve for the biomarkers neopterin in serum and myxovirus resistance protein 1 in blood. Both PD biomarkers increased following product administration with clear separation from baseline (neopterin: 3.4‐fold and 3.9‐fold increase for interferon β‐1a and pegylated interferon β‐1a, respectively; myxovirus resistance protein 1: 19.0‐fold and 47.2‐fold increase for interferon β‐1a and pegylated interferon β‐1a, respectively). The dose–response curves support that therapeutic doses were adequately sensitive to detect differences in both PD biomarkers for consideration in a PD similarity study design. Because baseline levels of both biomarkers are low compared with on‐treatment values, there was little difference in using PD measures adjusted to baseline compared with the results without baseline adjustment. This study illustrates potential methodologies for evaluating PD biomarkers and an approach to address information gaps when limited information is publicly available for one or more PD biomarkers. [ABSTRACT FROM AUTHOR]

Proteomics has the potential to identify pharmacodynamic (PD) biomarkers for similarity assessment of proposed biosimilars without relying on clinical efficacy end points. In this study, with 36 healthy participants randomized to therapeutic doses of interferon‐beta 1a products (IFNβ‐1a) or pegylated‐IFNβ‐1a (pegIFNβ‐1a) approved to treat multiple sclerosis or placebo, we evaluated the utility of a proteomic assay that profiles > 7,000 plasma proteins. IFNβ‐1a and pegIFNβ‐1a resulted in 248 and 528 differentially expressed protein analytes, respectively, between treatment and placebo groups over the time course. Thirty‐one proteins were prioritized based on a maximal fold change ≥ 2 from baseline, baseline adjusted area under the effect curve (AUEC) and overlap between the 2 products. Of these, the majority had a significant AUEC compared with placebo in response to either product; 8 proteins showed > 4‐fold maximal change from baseline. We identified previously reported candidates, beta‐2microglobulin and interferon‐induced GTP‐binding protein (Mx1) with ~ 50% coefficient of variation (CV) for AUEC, and many new candidates (including I‐TAC, C1QC, and IP‐10) with CVs ranging from 26%–129%. Upstream regulator analysis of differentially expressed proteins predicted activation of IFNβ1 signaling as well as other cytokine, enzyme, and transcription signaling networks by both products. Although independent replication is required to confirm present results, our study demonstrates the utility of proteomics for the identification of individual and composite candidate PD biomarkers that may be leveraged to support clinical pharmacology studies for biosimilar approvals, especially when biologics have complex mechanisms of action or do not have previously characterized PD biomarkers. [ABSTRACT FROM AUTHOR]

The US Food and Drug Administration (FDA) guidance describes how pharmacodynamic (PD) biomarkers can be used to address residual uncertainty and demonstrate no clinically meaningful differences between a proposed biosimilar and its reference product without relying on clinical efficacy end point(s). Pilot studies and modeling can inform dosing for such PD studies. To that end, we conducted a randomized, double‐blinded, placebo‐controlled, single‐dose, parallel‐arm clinical study in healthy participants to evaluate approaches to address information gaps, inform best practices for analysis of biomarker samples and study results, and apply emerging technologies in biomarker characterization. Seventy‐two healthy participants (n = 8 per arm) received either placebo or 1 of 4 doses of the interleukin‐5 inhibitors mepolizumab (3–24 mg) or reslizumab (0.1–0.8 mg/kg). A clinical study using doses lower than approved therapeutic doses was combined with modeling and simulation to evaluate the dose–response relationship of the biomarker eosinophils. There was no dose–response relationship for eosinophil counts due to variability, although the mepolizumab 24 mg and reslizumab 0.8 mg/kg doses showed clear effects. Published indirect‐response models were used to explore eosinophil data across doses from this study and the unstudied therapeutic doses. Simulations were used to calculate typical PD metrics, such as baseline‐adjusted area under the effect curve and maximum change from baseline. The simulation results demonstrate sensitivity of eosinophils as a PD biomarker and indicate doses lower than the approved doses would have PD responses overlapping with variability in the placebo arm. The simulation results further highlight the utility of model‐based approaches in supporting use of PD biomarkers in biosimilar development. [ABSTRACT FROM AUTHOR]

Objective: Employ the hollow fiber infection model (HFIM) to study sequential antibiotic administration (ampicillin, ciprofloxacin and fosfomycin) using human pharmacokinetic profiles to measure changes in the rate of antibiotic resistance development and compare this to simultaneous combination therapy with the same antibiotic combinations. Methods: Escherichia coli CFT073, a clinical uropathogenic strain, was exposed individually to clinically relevant pharmacokinetic concentrations of ampicillin on day 1, ciprofloxacin on day 2 and fosfomycin on day 3. This sequence was continued for 10 days in the HFIM. Bacterial samples were collected at different time points to enumerate total and resistant bacterial populations. The results were compared with the simultaneous combination therapy previously studied. Results: Sequential antibiotic treatment (ampicillin-ciprofloxacin-fosfomycin sequence) resulted in the early emergence of single and multi-antibiotic-resistant subpopulations, while the simultaneous treatment regimen significantly delayed or prevented the emergence of resistant subpopulations. Conclusion: Sequential administration of these antibiotic monotherapies did not significantly delay the emergence of resistant subpopulations compared to simultaneous treatment with combinations of the same antibiotics. Further studies are warranted to evaluate different sequences of the same antibiotics in delaying emergent resistance. [ABSTRACT FROM AUTHOR]

With the ongoing global pandemic of coronavirus disease 2019 (COVID‐19), there is an urgent need to accelerate the traditional drug development process. Many studies identified potential COVID‐19 therapies based on promising nonclinical data. However, the poor translatability from nonclinical to clinical settings has led to failures of many of these drug candidates in the clinical phase. In this study, we propose a mechanism‐based, quantitative framework to translate nonclinical findings to clinical outcome. Adopting a modularized approach, this framework includes an in silico disease model for COVID‐19 (virus infection and human immune responses) and a pharmacological component for COVID‐19 therapies. The disease model was able to reproduce important longitudinal clinical data for patients with mild and severe COVID‐19, including viral titer, key immunological cytokines, antibody responses, and time courses of lymphopenia. Using remdesivir as a proof‐of‐concept example of model development for the pharmacological component, we developed a pharmacological model that describes the conversion of intravenously administered remdesivir as a prodrug to its active metabolite nucleoside triphosphate through intracellular metabolism and connected it to the COVID‐19 disease model. After being calibrated with the placebo arm data, our model was independently and quantitatively able to predict the primary endpoint (time to recovery) of the remdesivir clinical study, Adaptive Covid‐19 Clinical Trial (ACTT). Our work demonstrates the possibility of quantitatively predicting clinical outcome based on nonclinical data and mechanistic understanding of the disease and provides a modularized framework to aid in candidate drug selection and clinical trial design for COVID‐19 therapeutics. [ABSTRACT FROM AUTHOR]

In vitro cell‐based data can be used to support the extension of pharmaceutical approval to patient subsets with unique genetic variants. A set of conditions should be satisfied to support the extension of approval. The disease mechanism should be well described, and the impact of variants on protein function should be reasonably understood. The incidence data should show that clinical trials for the variants in question are not practical. The overall safety and efficacy of the drug should be clear in adequate and well‐controlled clinical trials. The clinical trial should include patients found to be responders and nonresponders so that both positive and negative predictive power of the in vitro assay may be measured. The mechanism of action of the drug should be clearly defined and should be consistent with the disease mechanism. The assay system should be qualified, including the following points: (i) each variant construct should be confirmed by bidirectional sequencing; (ii) the in vitro assay should directly measure the variant protein function in comparison with the reference protein; (iii) the assay should be formally validated to the extent possible, clearly demonstrating precision, reproducibility, and sensitivity used to support the efficacy claim; and (iv) the primary data should be available for inspection and analytical validation. The overall goal is a robust and validated cell‐based system that can be shown to predict the outcome of targeted therapy. [ABSTRACT FROM AUTHOR]

Following a decision to require label warnings for concurrent use of opioids and benzodiazepines and increased risk of respiratory depression and death, the US Food and Drug Administratioin (FDA) recognized that other sedative psychotropic drugs may be substituted for benzodiazepines and be used concurrently with opioids. In some cases, data on the ability of these alternatives to depress respiration alone or in conjunction with an opioid are lacking. A nonclinical in vivo model was developed that could detect worsening respiratory depression when a benzodiazepine (diazepam) was used in combination with an opioid (oxycodone) compared to the opioid alone based on an increased arterial partial pressure of carbon dioxide (pCO2). The current study used that model to assess the impact on respiration of non‐benzodiazepine sedative psychotropic drugs representative of different drug classes (clozapine, quetiapine, risperidone, zolpidem, trazodone, carisoprodol, cyclobenzaprine, mirtazapine, topiramate, paroxetine, duloxetine, ramelteon, and suvorexant) administered alone and with oxycodone. At clinically relevant exposures, paroxetine, trazodone, and quetiapine given with oxycodone significantly increased pCO2 above the oxycodone effect. Analyses indicated that most pCO2 interaction effects were due to pharmacokinetic interactions resulting in increased oxycodone exposure. Increased pCO2 recorded with oxycodone‐paroxetine co‐administration exceeded expected effects from only drug exposure suggesting another mechanism for the increased pharmacodynamic response. This study identified drug‐drug interaction effects depressing respiration in an animal model when quetiapine or paroxetine were co‐administered with oxycodone. Clinical pharmacodynamic drug interaction studies are being conducted with these drugs to assess translatability of these findings. [ABSTRACT FROM AUTHOR]

A critical step to evaluate the potential in vivo antiviral activity of a drug is to connect the in vivo exposure to its in vitro antiviral activity. The Anti–SARS‐CoV‐2 Repurposing Drug Database is a database that includes both in vitro anti–SARS‐CoV‐2 activity and in vivo pharmacokinetic data to facilitate the extrapolation from in vitro antiviral activity to potential in vivo antiviral activity for a large set of drugs/compounds. In addition to serving as a data source for in vitro anti–SARS‐CoV‐2 activity and in vivo pharmacokinetic information, the database is also a calculation tool that can be used to compare the in vitro antiviral activity with in vivo drug exposure to identify potential anti–SARS‐CoV‐2 drugs. Continuous development and expansion are feasible with the public availability of this database. [ABSTRACT FROM AUTHOR]

Checkpoint inhibitors represent a new class of therapeutics in the treatment of cancer that has demonstrated remarkable clinical effectiveness. However, some patients have experienced serious immune-mediated adverse effects including pneumonitis, hepatitis, colitis, nephritis, dermatitis, encephalitis, and adrenal or pituitary insufficiency. These adverse events were not predicted by nonclinical studies. To determine if bone marrow-liver-thymus (BLT) immune humanized mice could demonstrate these adverse effects, we studied the effect of nivolumab on 2 strains of BLT-humanized mice, NOD.Cg-Prkdcscid Il2rgtm1Sug/JicTac (NOG) and NOD.Cg-Prkdcscid Il2rgtm1Sug Tg(SV40/HTLV-IL3, CSF2)10-7Jic/JicTac (NOG-EXL). Mice were treated with 2.5, 5.0, or 10.0 mg/kg nivolumab or saline twice weekly for 28 days. BLT-NOG mice had significantly reduced survival compared with BLT-NOG-EXL mice. In spite of the difference in survival, both BLT-humanized strains showed adverse reactions similar to those reported in humans, including pneumonitis and hepatitis, with nephritis, dermatitis and adrenalitis also noted in some individuals. Additional histopathologic findings included pancreatic atrophy, myositis, and osteomyelitis in some animals. T-cell activation increased with concomitant loss of PD-1 detection. These findings show that BLT immune humanized mice can demonstrate immune-mediated adverse effects of antiPD1 therapy, and may represent a model that can be used to better understand toxicity of this class of drugs. [ABSTRACT FROM AUTHOR]

To ensure US patients realize the public health benefit of a robust, competitive market for biosimilar products, the US Food and Drug Administration (FDA) is focused on improving the efficiency of biosimilar development and approvals. As noted above and outlined in FDA guidance documents, biosimilars may be approved based on PK and PD biomarker data without a comparative clinical study with efficacy end point(s).[2] Reliance on PK and PD biomarker data allows for shorter and less costly clinical studies than can often be conducted in healthy participants. Under circumstances where an established and sensitive PD biomarker does not exist, there is an opportunity to explore and identify new PD biomarkers to facilitate the use of PD biomarker data in clinical pharmacology studies. [Extracted from the article]

Aim: The goal of this study was to determine whether bacterial clearance in a rodent model would be impaired upon exposure to gold, silver or silica nanoparticles (NPs). Materials & methods: Mice received weekly injections of NPs followed by a challenge of Listeria monocytogenes (LM). On days 3 and 10 after LM injections, the animals were sacrificed and their tissues were collected for elemental analysis, electron microscopy and LM count determination. Results: The untreated and NP-treated animals cleared LM at the same rate suggesting that bioaccumulation of NPs did not increase the animals' susceptibility to bacterial infection. Conclusion: The data from this study indicate that the bioaccumulation of NPs does not significantly affect the ability to react to a bacterial challenge. [ABSTRACT FROM AUTHOR]

Background: As nanoparticles (NPs) become more prevalent in the pharmaceutical industry, questions have arisen from both industry and regulatory stakeholders about the long term effects of these materials. This study was designed to evaluate whether gold (10 nm), silver (50 nm), or silica (10 nm) nanoparticles administered intravenously to mice for up to 8 weeks at doses known to be sub-toxic (non-toxic at single acute or repeat dosing levels) and clinically relevant could produce significant bioaccumulation in liver and spleen macrophages. Results: Repeated dosing with gold, silver, and silica nanoparticles did not saturate bioaccumulation in liver or spleen macrophages. While no toxicity was observed with gold and silver nanoparticles throughout the 8 week experiment, some effects including histopathological and serum chemistry changes were observed with silica nanoparticles starting at week 3. No major changes in the splenocyte population were observed during the study for any of the nanoparticles tested. Conclusions: The clinical impact of these changes is unclear but suggests that the mononuclear phagocytic system is able to handle repeated doses of nanoparticles. [ABSTRACT FROM AUTHOR]

The pharmaceutical industry is developing increasing numbers of drugs and diagnostics based on nanoparticles, and evaluating the immune response to these diverse formulations has become a challenge for scientists and regulatory agencies alike. An international panel of scientists and representatives from various agencies and companies reviewed the imitations of current tests at a workshop held at the National Cancer Institute in Frederick, Maryland. This article outlines practical strategies for identifying and controlling interferences in common evaluation methods and the implications for regulation. [ABSTRACT FROM AUTHOR]

An imaging spectrometer was designed and fabricated for recording far ultraviolet spectra from laser-produced plasmas with wavelengths as short as 155 nm. The spectrometer implements a Cassegrain telescope and two gratings in a tandem Wadsworth optical configuration that provides diffraction limited resolution. Spectral images were recorded from plasmas produced by the irradiation of various target materials by intense KrF laser radiation with 248 nm wavelength. Two pairs of high-resolution gratings can be selected for the coverage of two wavebands, one grating pair with 1800 grooves/mm and covering approximately 155–175 nm and another grating pair with 1200 grooves/mm covering 230–260 nm. The latter waveband includes the 248 nm KrF laser wavelength, and the former waveband includes the wavelength of the two-plasmon decay instability at 23 the KrF laser wavelength (165 nm). The detection media consist of a complementary metal oxide semiconductor imager, photostimulable phosphor image plates, and a linear array of 1 mm2 square silicon photodiodes with 0.4 ns rise time. The telescope mirrors, spectrometer gratings, and 1 mm2 photodiode were calibrated using synchrotron radiation, and this enables the measurement of the absolute emission from the laser-produced plasmas with temporal, spatial, and spectral resolutions. The spectrometer is capable of measuring absolute spectral emissions at 165 nm wavelength as small as 5×10-7 J/nm from a plasma source area of 0.37 mm2 and with 0.4 ns time resolution. [ABSTRACT FROM AUTHOR]

Histopathological and immunohistochemical studies were conducted to characterize vascular injuries in rats treated with phosphodiesterase (PDE) IV inhibitors SCH 351591 or SCH 534385. Sprague-Dawley rats were administered PDE IV inhibitors by gavage at a range of doses and times. The two PDE IV inhibitors induced comparable levels of vascular injury, primarily in the mesentery and to a lesser extent in the pancreas, kidney, liver, small intestine, and stomach. Mesenteric vascular changes occurred as early as one hour, progressively developed over twenty-four to forty-eight hours, peaked at seventy-two hours, and gradually subsided from seven to nine days. The typical morphology of the vascular toxicity consisted of hemorrhage and necrosis of arterioles and arteries, microvascular injury, fibrin deposition, and perivascular inflammation of a variety of blood vessels. The incidence and severity of mesenteric vascular injury increased in a time- and dose-dependent manner in SCH 351591- or SCH 534385- treated rats. Mesenteric vascular injury was frequently associated with activation of mast cells (MC), endothelial cells (EC), and macrophages (MØ). Immunohistochemical studies showed increases in CD63 immunoreactivity of mesenteric MC and in nitrotyrosine immunoreactivity of mesenteric EC and MØ. The present study also provides a morphological and cellular basis for evaluating candidate biomarkers of drug-induced vascular injury. [ABSTRACT FROM AUTHOR]

Drug-induced phospholipidosis (PL) is a condition characterized by the accumulation of phospholipids and drug in lysosomes, and is found in a variety of tissue types. PL is frequently manifested in preclinical studies and may delay or prevent the development of pharmaceuticals. This report describes the construction of a database of PL findings in a variety of animal species and its use as a training data set for computational toxicology software. PL data and chemical structures were compiled from the published literature, existing pharmaceutical databases, and Food and Drug Administration (FDA) internal reports yielding a total of 583 compounds suitable for modeling. The database contained 190 (33%) positive drugs and 393 (77%) negative drugs, of which 39 were electron microscopy-confirmed negative compounds and 354 were classified as negatives due to the absence of positive reported data. Of the 190 positive findings, 76 were electron microscopy confirmed and 114 were considered positive based on other evidence. Quantitative structure-activity relationship (QSAR) models were constructed using two commercially available software programs, MC4PC and MDL-QSAR, and internal cross-validation (10 × 10%) experiments were performed to assess their predictive performance. Performance parameters for the MC4PC model were specificity 92%, sensitivity 50%, concordance 78%, positive predictivity 76%, and negative predictivity 78%. For MDL-QSAR, predictive performance was similar: specificity 80%, sensitivity 76%, concordance 79%, positive predictivity 65%, and negative predictivity 87%. By combining the output of the two QSAR programs, the overall predictive performance was vastly improved and sensitivity could be optimized to 81% without significant loss of specificity (79%). Many of the structural alerts and significant molecular descriptors obtained from the QSAR software were found to be associated with parts of active molecules known for their cationic amphiphilic drug (CAD) properties supporting the hypothesis that the endpoint of PL is statistically correlated with chemical structure. QSAR models can be useful tools for screening drug candidate molecules for potential PL. [ABSTRACT FROM AUTHOR]