Cancer is a group of disorders characterized by uncontrolled cell growth that affects around 11 million people each year globally. Nanocarrier-based systems are extensively used in cancer imaging, diagnostics as well as therapeutics; owing to their promising features and potential to augment therapeutic efficacy. The focal point of research remains to develop new-fangled smart nanocarriers that can selectively respond to cancer-specific conditions and deliver medications to target cells efficiently. Nanocarriers deliver loaded therapeutic cargos to the tumour site either in a passive or active mode, with the least drug elimination from the drug delivery systems. This review chiefly focuses on current advances allied to smart nanocarriers such as dendrimers, liposomes, mesoporous silica nanoparticles, quantum dots, micelles, superparamagnetic iron-oxide nanoparticles, gold nanoparticles and carbon nanotubes, to list a few. Exhaustive discussion on crucial topics like drug targeting, surface decorated smart-nanocarriers and stimuli-responsive cancer nanotherapeutics responding to temperature, enzyme, pH and redox stimuli have been covered.

To minimize the unwanted toxic effects of anti-anginal ranolazine by kinetic control of drug release, it was entrapped into gastro-resistant, biodegradable eudragit (EU) and ethyl cellulose (EC) binary blend using phase separation method. Ten formulations were prepared using different polymer blend ratios and solvent. The prepared microparticles were characterized for micromeritic properties, polymer drug compatibility by Fourier Transform Infrared Spectroscopy (FT-IR) and Differential Scannibg Calorimetry (DSC), and surface morphology by Scanning Electron Micrography (SEM). The yield of microparticles was up to 90% and more than 98% of the isolated microparticles are having volume mean diameter of 285 μm. The obtained angle of repose, percentage Carr's index and tapped density values were within the limits indicating good flow properties. The surface morphology revealed that particles were free-flowing, spherical, with minute pores and invert dents on the surface. The prepared microparticles were evaluated for percentage yield, encapsulation efficiency and in vitro release studies. FT-IR and DSC studies showed no chemical interaction between the drug and used polymers The in vitro drug release studies were carried out using pH 1.2 acid buffer and pH 7.4 phosphate buffer. EU acts as an excellent pH-dependent binder and helps to release the drug in the intestine. The drug release kinetics followed different transport mechanisms. Increasing the weight fractions of EU and decreased EC helps to control the drug release from the particles. From the differential (f1) and similarity factor (f2), Formulation F5 was the formulation most similar to the commercially available oral formulation as reference standard. The drug release performance was greatly affected by the materials used in microparticle preparations, which allow absorption in the intestinal tract.

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Adaptation towards digitalization in pharmaceuticals leads to the utilization and development of Artificial Intelligence (AI). Significantly it is reducing human workload with the help of an algorithm. Already AI is acting as a key in clinical trial, health care, quality management, manufacturing, product development, and management. Top pharmaceutical companies have adopted AI in different applications within the pharma sector. Different AI models like Machine learning, Artificial Neural Network, Deep Learning, robotics, and Natural Language Processing are being used in pharmaceuticals and healthcare systems. The Worldwide AI market is growing remarkably with a compound annual growth rate of 49.6% and is expected to reach $18,119 million by 2025. So, for better regulation, concerning safety, privacy regulatory strategy is heading towards a better framework. Different regulatory authorities like China, Europe, and United States (US) have adopted AI for economic and policy aspects. Emerging countries are using these tools for administrative work. US has begun implementing frameworks for AI adaptation, research, and development. The AI policy strategy started in 2016 with a series of workshops conducted under the Obama administration. Federal Food and Drug Administration (FDA) has also published draft guidance for regulatory oversight of AI and Machine Learning. In 2021 FDA published a draft regulation for software as a medical device. This review article provides a snapshot of AI implementation in pharmaceuticals and health care with the regulatory approach in the US.