Brain organoids are important models for mimicking some three-dimensional (3D) cytoarchitectural and functional aspects of the brain. Multielectrode arrays (MEAs) that enable recording and stimulation of activity from electrogenic cells offer notable potential for interrogating brain organoids. However, conventional MEAs, initially designed for monolayer cultures, offer limited recording contact area restricted to the bottom of the 3D organoids. Inspired by the shape of electroencephalography caps, we developed miniaturized wafer-integrated MEA caps for organoids. The optically transparent shells are composed of self-folding polymer leaflets with conductive polymer–coated metal electrodes. Tunable folding of the minicaps’ polymer leaflets guided by mechanics simulations enables versatile recording from organoids of different sizes, and we validate the feasibility of electrophysiology recording from 400- to 600-μm-sized organoids for up to 4 weeks and in response to glutamate stimulation. Our studies suggest that 3D shell MEAs offer great potential for high signal-to-noise ratio and 3D spatiotemporal brain organoid recording.

Amoxicillin is widely used to treat bacterial infections in neonates. However, considerable intercenter variability in dosage regimens of antibiotics exists in clinical practice. The pharmacokinetics of amoxicillin has been described in only a few preterm neonates. Thus, we aimed to evaluate the population pharmacokinetics of amoxicillin through a large sample size covering the entire age range of neonates and young infants and to establish evidence-based dosage regimens based on developmental pharmacokinetics-pharmacodynamics. This is a prospective, multicenter, pharmacokinetic study using an opportunistic sampling design. Amoxicillin plasma concentrations were determined using high-performance liquid chromatography. Population pharmacokinetic analysis was performed using NONMEM. A total of 224 pharmacokinetic samples from 187 newborns (postmenstrual age range, 28.4 to 46.3 weeks) were available for analysis. A two-compartment model with first-order elimination was used to describe population pharmacokinetics. Covariate analysis showed that current weight, postnatal age, and gestational age were significant covariates. The final model was further validated for predictive performance in an independent cohort of patients. Monte Carlo simulation demonstrated that for early-onset sepsis, the currently used dosage regimen (25 mg/kg twice daily [BID]) resulted in 99.0% of premature neonates and 87.3% of term neonates achieving the pharmacodynamic target (percent time above MIC), using a MIC breakpoint of 1 mg/liter. For late-onset sepsis, 86.1% of premature neonates treated with 25 mg/kg three times a day (TID) and 79.0% of term neonates receiving 25 mg/kg four times a day (QID) reached the pharmacodynamic target, using a MIC breakpoint of 2 mg/liter. The population pharmacokinetics of amoxicillin was assessed in neonates and young infants. A dosage regimen was established based on developmental pharmacokinetics-pharmacodynamics.

The blood concentration of isoniazid (INH) is evidently affected by polymorphisms in N-acetyltransferase 2 (NAT2), an enzyme that is primarily responsible for the trimodal (i.e., fast, intermediate, and slow) INH elimination. The pharmacokinetic (PK) variability, driven largely by NAT2 activity, creates a challenge for the deployment of a uniform INH dosage in tuberculosis (TB) patients. Although acetylator-specific INH dosing has long been suggested, well-recognized dosages according to acetylator status remain elusive. In this study, 175 blood samples were collected from 89 pulmonary TB patients within 0.5 to 6 h after morning INH administration. According to their NAT2 genotypes, 32 (36.0%), 38 (42.7%), and 19 (21.3%) were fast, intermediate, and slow acetylators, respectively. The plasma INH concentration was detected by liquid chromatography-tandem mass spectrometry. Population pharmacokinetic (PPK) analysis was conducted using NONMEM and R software. A two-compartment model with first-order absorption and elimination well described the PK parameters of isoniazid. Body weight and acetylator status significantly affected the INH clearance rate. The dosage simulation targeting three indicators, including the well-recognized efficacy-safety indicator maximum concentration in serum (Cmax; 3 to 6 μg/ml), the reported area under the concentration-time curve from 0 h to infinity (AUC0–∞; ≥10.52 μg·h/ml), and the 2-h INH serum concentrations (≥2.19 μg/ml), was associated with the strongest early bactericidal activity. The optimal dosages targeting the different indicators varied from 700 to 900 mg/day, 500 to 600 mg/day, and 300 mg/day for the rapid, intermediate, and slow acetylators, respectively. Furthermore, a PPK model for isoniazid among Chinese tuberculosis patients was established for the first time and suggested doses of approximately 800 mg/day, 500 mg/day, and 300 mg/day for fast, intermediate, and slow acetylators, respectively, after a trade-off between efficacy and the occurrence of side effects.

Recent advances in human stem cell-derived brain organoids promise to replicate critical molecular and cellular aspects of learning and memory and possibly aspects of cognition in vitro. Coining the term “organoid intelligence” (OI) to encompass these developments, we present a collaborative program to implement the vision of a multidisciplinary field of OI. This aims to establish OI as a form of genuine biological computing that harnesses brain organoids using scientific and bioengineering advances in an ethically responsible manner. Standardized, 3D, myelinated brain organoids can now be produced with high cell density and enriched levels of glial cells and gene expression critical for learning. Integrated microfluidic perfusion systems can support scalable and durable culturing, and spatiotemporal chemical signaling. Novel 3D microelectrode arrays permit high-resolution spatiotemporal electrophysiological signaling and recording to explore the capacity of brain organoids to recapitulate the molecular mechanisms of learning and memory formation and, ultimately, their computational potential. Technologies that could enable novel biocomputing models via stimulus-response training and organoid-computer interfaces are in development. We envisage complex, networked interfaces whereby brain organoids are connected with real-world sensors and output devices, and ultimately with each other and with sensory organ organoids (e.g. retinal organoids), and are trained using biofeedback, big-data warehousing, and machine learning methods. In parallel, we emphasize an embedded ethics approach to analyze the ethical aspects raised by OI research in an iterative, collaborative manner involving all relevant stakeholders. The many possible applications of this research urge the strategic development of OI as a scientific discipline. We anticipate OI-based biocomputing systems to allow faster decision-making, continuous learning during tasks, and greater energy and data efficiency. Furthermore, the development of “intelligence-in-a-dish” could help elucidate the pathophysiology of devastating developmental and degenerative diseases (such as dementia), potentially aiding the identification of novel therapeutic approaches to address major global unmet needs.