Nanoparticles (NPs) are atomic clusters of crystalline or amorphous structure that possess unique physical and chemical properties associated with a size range of between 1 and 100 nm. Their nano-sized dimensions, which are in the same range as those of vital biomolecules, such as antibodies, membrane receptors, nucleic acids, and proteins, allow them to interact with different structures within living organisms. Because of these features, numerous nanoparticles are used in medicine as delivery agents for biomolecules. However, off-target drug delivery can cause serious side effects to normal tissues and organs. Considering this issue, it is essential to develop bioengineering strategies to significantly reduce systemic toxicity and improve therapeutic effect. In contrast to passive delivery, nanosystems enable to obtain enhanced therapeutic efficacy, decrease the possibility of drug resistance, and reduce side effects of “conventional” therapy in cancers. The present review provides an overview of the most recent (mostly last 3 years) achievements related to different biomolecules used to enable targeting capabilities of highly diverse nanoparticles. These include monoclonal antibodies, receptor-specific peptides or proteins, deoxyribonucleic acids, ribonucleic acids, [DNA/RNA] aptamers, and small molecules such as folates, and even vitamins or carbohydrates.

Extracellular vesicles (EVs) hold great promise for clinical application as new diagnostic and therapeutic modalities. This paper describes major GMP-based upstream and downstream manufacturing processes for EV large-scale production, also focusing on post-processing technologies such as surface bioengineering and uploading studies to yield novel EV-based diagnostics and advanced therapy medicinal products. This paper also focuses on the quality, safety, and efficacy issues of the bioengineered EV drug candidates before first-in-human studies. Because clinical trials involving extracellular vesicles are on the global rise, this paper encompasses different clinical studies registered on clinical-trial register platforms, with varying levels of advancement, highlighting the growing interest in EV-related clinical programs. Navigating the regulatory affairs of EVs poses real challenges, and obtaining marketing authorization for EV-based medicines remains complex due to the lack of specific regulatory guidelines for such novel products. This paper discusses the state-of-the-art regulatory knowledge to date on EV-based diagnostics and medicinal products, highlighting further research and global regulatory needs for the safe and reliable implementation of bioengineered EVs as diagnostic and therapeutic tools in clinical settings. Post-marketing pharmacovigilance for EV-based medicinal products is also presented, mainly addressing such topics as risk assessment and risk management.

A chemical property space defines the adaptability of a molecule to changing conditions and its interaction with other molecular systems determining a pharmacological response. Within a congeneric molecular series (compounds with the same derivatization algorithm and thus the same brute formula) the chemical properties vary in a monotonic manner, i.e., congeneric compounds share the same chemical property space. The chemical property space is a key component in molecular design, where some building blocks are functionalized, i.e., derivatized, and eventually self-assembled in more complex systems, such as enzyme-ligand systems, of which (physico-chemical) properties/bioactivity may be predicted by QSPR/QSAR (quantitative structure-property/activity relationship) studies. The system structure is determined by the binding type (temporal/permanent; electrostatic/covalent) and is reflected in its local electronic (and/or magnetic) properties. Such nano-systems play the role of molecular devices, important in nano-medicine. In the present article, the behavior of polyethylenimine (PEI) macromolecules (linear LPEI and branched BPEI, respectively) with respect to the glucose oxidase enzyme GOx is described in terms of their (interacting) energy, geometry and topology, in an attempt to find the best shape and size of PEIs to be useful for a chosen (nanochemistry) purpose.

The incidence of lung cancer continues to rise worldwide. Because the aggressive metastasis of lung cancer cells is the major drawback of successful therapies, the crucial challenge of modern nanomedicine is to develop diagnostic tools to map the molecular mechanisms of metastasis in lung cancer patients. In recent years, microfluidic platforms have been given much attention as tools for novel point-of-care diagnostic, an important aspect being the reconstruction of the body organs and tissues mimicking the in vivo conditions in one simple microdevice. Herein, we present the first comprehensive overview of the microfluidic systems used as innovative tools in the studies of lung cancer metastasis including single cancer cell analysis, endothelial transmigration, distant niches migration and finally neoangiogenesis. The application of the microfluidic systems to study the intercellular crosstalk between lung cancer cells and surrounding tumor microenvironment and the connection with multiple molecular signals coming from the external cellular matrix are discussed. We also focus on recent breakthrough technologies regarding lab-on-chip devices that serve as tools for detecting circulating lung cancer cells. The superiority of microfluidic systems over traditional in vitro cell-based assays with regard to modern nanosafety studies and new cancer drug design and discovery is also addressed. Finally, the current progress and future challenges regarding printable and paper-based microfluidic devices for personalized nanomedicine are summarized.

The aims of this study were to assess the sensitivity of various magnetic resonance imaging (MRI) sequences for the diagnosis of pulmonary nodules and to estimate the accuracy of MRI for the measurement of lesion size, as compared to computed tomography (CT). Fifty patients with 113 pulmonary nodules diagnosed by CT underwent lung MRI and CT. MRI studies were performed on 1.5T scanner using the following sequences: T2-TSE, T2-SPIR, T2-STIR, T2-HASTE, T1-VIBE, and T1-out-of-phase. CT and MRI data were analyzed independently by two radiologists. The overall sensitivity of MRI for the detection of pulmonary nodules was 80.5% and according to nodule size: 57.1% for nodules ≤4mm, 75% for nodules >4-6mm, 87.5% for nodules >6-8mm and 100% for nodules >8mm. MRI sequences yielded following sensitivities: 69% (T1-VIBE), 54.9% (T2-SPIR), 48.7% (T2-TSE), 48.7% (T1-out-of-phase), 45.1% (T2-STIR), 25.7% (T2-HASTE), respectively. There was very strong agreement between the maximum diameter of pulmonary nodules measured by CT and MRI (mean difference -0.02 mm; 95% CI –1.6–1.57 mm; Bland-Altman analysis). MRI yielded high sensitivity for the detection of pulmonary nodules and enabled accurate assessment of their diameter. Therefore it may be considered an alternative to CT for follow-up of some lung lesions. However, due to significant number of false positive diagnoses, it is not ready to replace CT as a tool for lung nodule detection.

Objectives To compare the efficacy of two quantitative methods for discrimination between benign and malignant focal liver lesions (FLLs): apparent diffusion coefficient (ADC) values and T2 relaxation times. Methods Seventy-three patients with 215 confirmed FLLs (115 benign, 100 malignant) underwent 1.5-T MRI with respiratory-triggered single-shot SE DWI (b = 50, 400, 800) and dual-echo T2TSE (TR = 3,000 ms; TE1 = 84 ms; TE2 = 228 ms). ADC values and T2 relaxation times of FLLs were calculated. Sensitivity, specificity and accuracy of both techniques in diagnosing malignancy were assessed. Results The mean ADC value of malignant tumours (1.07 × 10⁻³ mm²/s) was significantly lower (P < 0.05) than that of benign lesions (1.86 × 10⁻³ mm²/s ); however, with the use of the optimal cut-off value of 1.25 × 10⁻³ mm²/s, 20 false positive (FP) and 20 false negative (FN) diagnoses of malignancy were noted, generating 79 % sensitivity, 82.6 % specificity and 80.9 % accuracy. The mean T2 relaxation time of malignant tumours (64.4 ms) was significantly lower (P < 0.05) than that of benign lesions (476.1 ms). At the threshold of 107 ms 22 FP and 1 FN diagnoses were noted; the sensitivity was 99 %, specificity 80.9 % and accuracy 89.3 %. Conclusions Quantitative analysis of T2 relaxation times yielded significantly higher sensitivity and accuracy in diagnosing malignant liver tumour than ADC values. Key Points • Diffusion-weighted magnetic resonance imaging is increasingly used for liver lesions. • But ADC values demonstrated only moderate accuracy for differentiation of liver lesions. • T2 relaxation times yielded higher accuracy in diagnosing malignant liver tumours. • Both ADC and T2 values overlapped between focal nodular hyperplasia and malignant lesions. • Nevertheless T2 liver mapping could be valuable for evaluating focal liver lesions.