Utilizing virtual experiments to increase understanding of discrepancies involving in vitro-to-in vivo predictions of hepatic clearance.

Predictions of xenobiotic hepatic clearance in humans using in vitro-to-in vivo extrapolation methods are frequently inaccurate and problematic. Multiple strategies are being pursued to disentangle responsible mechanisms. The objective of this work is to evaluate the feasibility of using insights gained from independent virtual experiments on two model systems to begin unraveling responsible mechanisms. The virtual culture is a software analog of hepatocytes in vitro, and the virtual human maps to hepatocytes within a liver within an idealized model human. Mobile objects (virtual compounds) map to amounts of xenobiotics. Earlier versions of the two systems achieved quantitative validation targets for intrinsic clearance (virtual culture) and hepatic clearance (virtual human). The major difference between the two systems is the spatial organization of the virtual hepatocytes. For each pair of experiments (virtual culture, virtual human), hepatocytes are configured the same. Probabilistic rules govern virtual compound movements and interactions with other objects. We focus on highly permeable virtual compounds and fix their extracellular unbound fraction at one of seven values (0.05-1.0). Hepatocytes contain objects that can bind and remove compounds, analogous to metabolism. We require that, for a subset of compound properties, per-hepatocyte compound exposure and removal rates during culture experiments directly predict corresponding measures made during virtual human experiments. That requirement serves as a cross-system validation target; we identify compound properties that enable achieving it. We then change compound properties, ceteris paribus, and provide model mechanism-based explanations for when and why measures made during culture experiments under- (or over-) predict corresponding measures made during virtual human experiments. The results show that, from the perspective of compound removal, the organization of hepatocytes within virtual livers is more efficient than within cultures, and the greater the efficiency difference, the larger the underprediction. That relationship is noteworthy because most in vitro-to-in vivo extrapolation methods abstract away the structural organization of hepatocytes within a liver. More work is needed on multiple fronts, including the study of an expanded variety of virtual compound properties. Nevertheless, the results support the feasibility of the approach and plan.

Contrasting model mechanisms of alanine aminotransferase (ALT) release from damaged and necrotic hepatocytes as an example of general biomarker mechanisms.

Interpretations of elevated blood levels of alanine aminotransferase (ALT) for drug-induced liver injury often assume that the biomarker is released passively from dying cells. However, the mechanisms driving that release have not been explored experimentally. The usefulness of ALT and related biomarkers will improve by developing mechanism-based explanations of elevated levels that can be expanded and elaborated incrementally. We provide the means to challenge the ability of closely related model mechanisms to generate patterns of simulated hepatic injury and ALT release that scale (or not) to be quantitatively similar to the wet-lab validation targets, which are elevated plasma ALT values following acetaminophen (APAP) exposure in mice. We build on a published model mechanism that helps explain the generation of characteristic spatiotemporal features of APAP hepatotoxicity within hepatic lobules. Discrete event and agent-oriented software methods are most prominent. We instantiate and leverage a small constellation of concrete model mechanisms. Their details during execution help bring into focus ways in which particular sources of uncertainty become entangled with cause-effect details within and across several levels. We scale ALT amounts in virtual mice directly to target plasma ALT values in individual mice. A virtual experiment comprises a set of Monte Carlo simulations. We challenge the sufficiency of four potentially explanatory theories for ALT release. The first of the tested model theories failed to achieve the initial validation target, but each of the three others succeeded. Results for one of the three model mechanisms matched all target ALT values quantitatively. It explains how ALT externalization is the combined consequence of lobular-location-dependent drug-induced cellular damage and hepatocyte death. Falsification of one (or more) of the model mechanisms provides new knowledge and incrementally shrinks the constellation of model mechanisms. The modularity and biomimicry of our explanatory models enable seamless transition from mice to humans.

Developing a model to predict unfavourable treatment outcomes in patients with tuberculosis and human immunodeficiency virus co-infection in Delhi, India.

BACKGROUND: Tuberculosis (TB) patients with human immunodeficiency virus (HIV) co-infection have worse TB treatment outcomes compared to patients with TB alone. The distribution of unfavourable treatment outcomes differs by socio-demographic and clinical characteristics, allowing for early identification of patients at risk. OBJECTIVE: To develop a statistical model that can provide individual probabilities of unfavourable outcomes based on demographic and clinical characteristics of TB-HIV co-infected patients. METHODOLOGY: We used data from all TB patients with known HIV-positive test results (aged ≥15 years) registered for first-line anti-TB treatment (ATT) in 2015 under the Revised National TB Control Programme (RNTCP) in Delhi, India. We included variables on demographics and pre-treatment clinical characteristics routinely recorded and reported to RNTCP and the National AIDS Control Organization. Binomial logistic regression was used to develop a statistical model to estimate probabilities of unfavourable TB treatment outcomes (i.e., death, loss to follow-up, treatment failure, transfer out of program, and a switch to drug-resistant regimen). RESULTS: Of 55,260 TB patients registered for ATT in 2015 in Delhi, 928 (2%) had known HIV-positive test results. Of these, 816 (88%) had drug-sensitive TB and were ≥15 years. Among 816 TB-HIV patients included, 157 (19%) had unfavourable TB treatment outcomes. We developed a model for predicting unfavourable outcomes using age, sex, disease classification (pulmonary versus extra-pulmonary), TB treatment category (new or previously treated case), sputum smear grade, known HIV status at TB diagnosis, antiretroviral treatment at TB diagnosis, and CD4 cell count at ATT initiation. The chi-square p-value for model calibration assessed using the Hosmer-Lemeshow test was 0.15. The model discrimination, measured as the area under the receiver operator characteristic (ROC) curve, was 0.78. CONCLUSION: The model had good internal validity, but should be validated with an independent cohort of TB-HIV co-infected patients to assess its performance before clinical or programmatic use.

Apigenin loaded nanoparticle delayed development of hepatocellular carcinoma in rats.

Hepatocellular carcinoma (HCC) is one of the major causes of cancer related death globally. Apigenin, a dietary flavonoid, possesses anti-tumor activity against HCC cells in-vitro. Development, physicochemical characterization of apigenin loaded nanoparticles (ApNp), biodistribution pattern and pharmacokinetic parameters of apigenin upon intravenous administration of ApNp, and effect of ApNp treatment in rats with HCC were investigated. Apigenin loaded nanoparticles had a sustained drug release pattern and successfully reached the hepatic cancer cells in-vitro as well as in liver of carcinogenic animals. ApNp predominantly delayed the progress of HCC in chemical induced hepatocarcinogenesis in rats. Quantification of apigenin by liquid chromatography-mass spectroscopy (LC-MS/MS) showed that apigenin availability significantly increased in blood and liver upon ApNp treatment. Apigenin loaded nanoparticle delivery substantially controlled the severity of hepatocellular carcinoma and could be a future hope for lingering the survival in hepatic cancer patients.

Lipid-based nanocarrier efficiently delivers highly water soluble drug across the blood-brain barrier into brain.

Delivering highly water soluble drugs across blood-brain barrier (BBB) is a crucial challenge for the formulation scientists. A successful therapeutic intervention by developing a suitable drug delivery system may revolutionize treatment across BBB. Efforts were given here to unravel the capability of a newly developed fatty acid combination (stearic acid:oleic acid:palmitic acid = 8.08:4.13:1) (ML) as fundamental component of nanocarrier to deliver highly water soluble zidovudine (AZT) as a model drug into brain across BBB. A comparison was made with an experimentally developed standard phospholipid-based nanocarrier containing AZT. Both the formulations had nanosize spherical unilamellar vesicular structure with highly negative zeta potential along with sustained drug release profiles. Gamma scintigraphic images showed both the radiolabeled formulations successfully crossed BBB, but longer retention in brain was observed for ML-based formulation (MGF) as compared to soya lecithin (SL)-based drug carrier (SYF). Plasma and brain pharmacokinetic data showed less clearance, prolonged residence time, more bioavailability and sustained release of AZT from MGF in rats compared to those data of the rats treated with SYF/AZT suspension. Thus, ML may be utilized to successfully develop drug nanocarrier to deliver drug into brain across BBB, in a sustained manner for a prolong period of time and may provide an effective therapeutic strategy for many diseases of brain. Further, many anti-HIV drugs cannot cross BBB sufficiently. Hence, the developed formulation may be a suitable option to carry those drugs into brain for better therapeutic management of HIV.

Variation of Pharmacokinetic Profiles of Some Antidiabetic Drugs from Nanostructured Formulations Administered Through Pulmonary Route.

BACKGROUND: Diabetes is a chronic disease that occurs when the pancreas does not produce enough insulin, or when the body cannot effectively use the insulin it produces. WHO projects that diabetes death will be doubled between 2005 and 2030, where 347 million people worldwide had diabetes as per the report of 2013. The increase in the prevalence of diabetes is due to three influences - lifestyle, ethnicity, and age. METHODS: The present review summarizes the pharmacokinetic parameters and challenges in the field of nanoparticles and nanoliposomes of insulin and other antidiabetic drugs given through pulmonary route to treat diabetes effectively. RESULTS: Current challenges in diabetes management include optimizing the use of the already available therapies to ensure adequate glycemic condition, blood pressure, lipid control and to reduce complications. At present, several pieces of research have been focusing on new management options for diabetes. Among these options, the use of nanomedicine is becoming an eye catching and most promising one. Currently, nanoparticles and nanoliposomes are thrust areas of research to treat any deadly disease like diabetes. These drug delivery systems ultimately result in longer circulation half-lives, improved drug pharmacokinetics, and reduced side effects of therapeutically active substances that may be insulin and non-insulin. CONCLUSIONS: Thus, the pulmonary route is the most promising alternative route of drug delivery since it is non-invasive and lungs have a large surface area, richly supplied by the capillary network, for absorption of drugs.

Nanoscale Formulations and Diagnostics With Their Recent Trends: A Major Focus of Future Nanotechnology.

Nanomedicine is an emerging and rapidly growing field, possibly exploring for high expectation to healthcare. Nanoformulations have been designed to overcome challenges due to the development and fabrication of nanostructures. Unique size-dependent properties of nanoformulations make them superior and indispensable in many areas of human activity. Nano drug delivery systems are formulated and engineered to carry and deliver a number of substances in a targeted and controlled way. The vision of nanocarriers can be designed that will serve a dual purpose, allowing both treatment and diagnosis to be contained in an 'all-in-one' package. Nanoscale drugdelivery systems efficiently regulate the release, pharmacokinetics, pharmacodynamics, solubility, immunocompatibility, cellular uptake and biodistribution of chemical entities (drug). Their cellular uptake takes place by various mechanisms such as micropinocytosis, phagocytosis and receptor mediated endocytosis. These phenomena cause longer retention in blood circulation resulting in the release of the encapsulated materials in a sustained manner thus minimize the plasma fluctuations and toxic side effects. In this manner, the therapeutic index of conventional pharmaceuticals is efficiently increased. They can be used to deliver both micro and macro biomolecules such as peptides, proteins, plasmid DNA and synthetic oligodeoxynucleotides. In this present review, several recent developing and modifying nano-products for the detection, analysis, and treatment of diseases with their US and world patents along with various diagnostic kits have been discussed.