Arsenic, in addition to being a confirmed carcinogen, is one of the most toxic elements found in nature, and should therefore be removed if the concentration is greater than 10 μg/L. Nanofiltration (NF) membranes have succeeded in arsenate As (V) ions removal from water almost completely. It is reported in this review that, like reverse osmosis (RO) membranes, NF membranes have not yet performed alone arsenite As (III) ion rejection without being associated with another technology. Commercial NF membranes exhibited a rejection between 86 and 99% towards arsenate As (V) while As (V) removal reached 99.8% for synthesized NF membranes. Since commercial NF membranes have shown their limit, scientists have prepared novel NF membranes that demonstrated long-term efficiency, fouling reduction, cost reduction, an increase in separation of multivalent ions, rejection performance, or a high flux achievement, depending on the area of use. For small treatment plants, NF is a more cost-effective method. The review succinctly reported arsenic as a serious global contamination issue and focused on novel nanofiltration processes for arsenic rejection to safeguard water security. This article also developed a comparative study of nanofiltration and reverse osmosis techniques concerning arsenic removal. Finally, future trends and perspectives have been highlighted with particular emphasis on emerging synthesis techniques of NF membranes without hiding the unpleasant fouling issue that limits its competitiveness.

A defect-free, loose, and strong layer consisting of zirconium (Zr) nanoparticles (NPs) has been successfully established on a polyacrylonitrile (PAN) ultrafiltration substrate by an in-situ formation process. The resulting organic–inorganic nanofiltration (NF) membrane, NF-PANZr, has been accurately characterized not only with regard to its properties but also its structure by the atomic force microscopy, field emission scanning electron microscopy, and energy dispersive spectroscopy. A sophisticated computing model consisting of the Runge–Kutta method followed by Richardson extrapolation was applied in this investigation to solve the extended Nernst–Planck equations, which govern the solute particles’ transport across the active layer of NF-PANZr. A smart, adaptive step-size routine is chosen for this simple and robust method, also known as RK4 (fourth-order Runge–Kutta). The NF-PANZr membrane was less performant toward monovalent ions, and its rejection rate for multivalent ions reached 99.3%. The water flux of the NF-PANZr membrane was as high as 58 L · m⁻² · h⁻¹. Richardson’s extrapolation was then used to get a better approximation of Cl⁻ and Mg²⁺ rejection, the relative errors were, respectively, 0.09% and 0.01% for Cl⁻ and Mg²⁺. While waiting for the rise and expansion of machine learning in the prediction of rejection performance, we strongly recommend the development of better NF models and further validation of existing ones.

Titanium (Ti) nanoparticles (NPs) were successfully seeded on the platform of a polyacrylonitrile (PAN) ultrafiltration (UF) membrane previously coated with bio-glue (a co-deposition of dopamine hydrochloric bicarbonate buffer having undergone pyrocatechol deprotonation). The tools in vogue, especially field emission scanning electron microscopy (FESEM), energy dispersive spectroscopy (EDS), and atomic force microscopy (AFM), have made it possible to fully characterize the structure of the new organic-inorganic nanofiltration (NF) membrane, namely NF_PAN_Ti. A soft computing model has been applied to make commonplace the complex and implicit extended Nernst–Planck equations that govern the transport of ions through NF membranes. Euler’s numerical method was applied with a small step-size and the results obtained were very interesting. The filtration velocity approach of GUEROUT-ELFORD-FERRY helped to estimate the average pore size of NF_PAN_Ti to r_p = 0.538 nm. A six-day test carried out on NF_PAN_Ti demonstrated its long-term stability and showed a steady-rejection rate of 89.3% of MgCl₂ salt and permeate flux of 56 L·m⁻²·h⁻¹. The Euler’ numerical method corroborated perfectly the experimental findings since the relative error was found to be very low at 0.33% for Cl⁻ and 0.09% for Mg²⁺ (RE << 0.1). These practical prediction tools may henceforth help in the choice and calibration of next-generation NF membranes’ synthesis.

A flawless, extremely loose, membrane, efficient for multivalent ions separation, has been successfully synthesized by the in-situ formation approach. The as-synthesized nanofiltration (NF) membrane, NF_PES-Zr, proceeded from a thin film layer of nanoparticles (NPs) zirconium that coated the platform of the polyethersulfone (PES) ultrafiltration (UF) membrane through a bio-glue made from dopamine hydrochloric and sodium bicarbonate buffer. The estimation of the average pore size of the novel organic-inorganic NF membrane NF_PES-Zr using the filtration velocity approach of Guerout-Elford-Ferry was close to 0.9 nm. NF_PES-Zr membrane holds a record in permeate water flux release of about 62.5 and was revealed to be effective for multivalent ions separation. A 5 days-test performed on NF_PES-Zr demonstrated its long-term stability and showed a rejection rate of 93.4% and 37.8% respectively for and .

The activated sludge process serves as the core barrier in pharmaceutical wastewater treatment, yet its stability is inherently challenged by the extreme complexity of influent composition and the unpredictability of toxic shocks, particularly under contract development and manufacturing organization (CDMO) operations. Current biotoxicity assessment methods face inherent trade-offs among timeliness, specificity, and matrix robustness, resulting in fragmented, reactive management that lacks predictive capacity. In response, this review critically synthesizes evidence on toxicity pathways and monitoring technologies, systematically evaluating their mechanistic basis and engineering applicability. Building on these findings, we propose a conceptual perception–cognition–response architecture that structures decision-making across three adaptive tiers: (i) a perception layer that tolerates false positives for rapid anomaly detection; (ii) a cognition layer that requires effect-based biological verification; and (iii) a response layer that authorizes resilience-oriented interventions. Rather than a linear pipeline, the three tiers form an adaptive feedback cycle that dynamically aligns monitoring intensity, verification depth, and response authority with real-time risk gradients and site-specific constraints. By explicitly linking biological mechanisms to assessment limitations and tiered decision rules, this review provides a hypothesis-generating roadmap that orients biotoxicity management from episodic, composition-based assessment toward adaptive, effect-driven control. The proposed framework is intended to guide future pilot validation, multi-sensor integration, and context-specific calibration, offering a unified narrative for advancing proactive biotoxicity control in complex pharmaceutical wastewater systems.