Morgan and McIver's weakest pre-expectation framework is one of the most well-established methods for deductive verification of probabilistic programs. Roughly, the idea is to generalize binary state assertions to real-valued expectations. While loop-free programs can be analyzed by mechanically transforming expectations, verifying loops usually requires finding an invariant expectation, a difficult task. We propose a new view of invariant expectation synthesis as a regression problem: given an input state, predict the average value of the postexpectation. Guided by this perspective, we develop the first data-driven invariant synthesis method for probabilistic programs. Unlike prior work on probabilistic invariant inference, our approach can learn piecewise continuous invariants without relying on template expectations, and also works when only given black-box access to the program. We implement our approach and demonstrate its effectiveness on a variety of benchmarks from the probabilistic programming literature.

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An easy, precise and accurate spectroscopic technique for the estimation of cyclosporine and dimethylfumarate in pure form and nano dosage form has been developed. The proposed method involves dissolving dimethylfumarate in distilled water and cyclosporine in ethanol and subjecting resulting solution to UV spectroscopic assessment. Absorption maximum was found 210 and 214 nm respectively. Beer’s law was obeyed in the concentration range of 1 to 5and 1 to 8 μg/mL for dimethylfumarate and cyclosporine. Calibration curve showd linearity between absorbance and concentration as per line equation with R2 value near 1. Validation was performed as ICH guildelines for linearity, accuracy, precision, Robustness, System suitability.

Aims/Objective: To formulate and evaluate RGD sequenced fibrin/fibrinogen based nanoscaffolds (acid-labile linker) for the treatment of brain tumor targeting to achieve an acid-triggered drug release under a mild acidic condition in tumor. Place and Duration of Study: Department of Pharmaceutics, Parul Institute of Pharmacy and Research, Parul University, Vadodara, between 2017 to 2021. Methodology: Nanoscaffolds was prepared with Drug–linker–Fbg conjugate solution, using modified water-in-oil (W/O) emulsification/solvent extraction method. The conjugate solution was constantly injected in soya lecithin (100 ml) using a syringe (1 ml/min) and stirred using Magnetic stirrer for 30 minutes to form stable a W/O emulsion. The present investigation was aimed to evaluate with Particle size, Zeta potential measurement, Percent drug entrapment, Transmission electron microscopy. Results:  As per Evaluation parameters were performed such as Particle size measured as 151.8±2.02 nm to 157.4 ± 3.81 nm. Zeta Potential was found that -37.1±6.32, Percent Drug Entrapment was 91.4±0.37 which indicates that the drug release of lyophilised FBG based nanoscaffolds was indicatively higher as compared to FBG based nanoscaffolds (alone). Conclusion: As per the study design the formulated nanoscaffolds were found to impart the drug release based on their particle size and percent drug entrapment and hence fights against cancer cells in brain by their EDC-NHS chemistry. Drug of choice Everolimus along with Fbg based nanoscaffolds offers better biocompatibility by exposing dual responsiveness at acidic environment in tumors. The results of in-vitro drug release reveals the better uptake of drug at targeted site of action.

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