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Immune Modulator

Adamax

Also known as: N-acetyl Semax amidate adamantylated

Adamax is a grey-market nootropic peptide developed and sold by the Mexico-based vendor Ceretropic. It is marketed as a Semax derivative: N-acetyl Semax amide (Ac-MEHFPGP-NH2) with an adamantane (adamantyl-glycine) moiety appended at the C-terminus, reportedly intended to improve metabolic stability and blood-brain-barrier penetration. It is NOT an ADNP / NAP / davunetide analog despite some online descriptions conflating it with those compounds. Adamax has no indexed peer-reviewed literature of its own; all claimed effects are extrapolated from Semax data plus anecdotal user reports.

Real-time market data

Pricing for Adamax

Live vendor pricing, normalized to $/mg so sizes compare fairly — fused with each seller's Merit trust score and latest independent COA purity. Prices refresh daily.

Research depth

15 citations indexed for Adamax

All research on Adamax →

Study · 2026

A robust stacked ensemble strategy with multi-optimizer CNN models for skin cancer classification

Skin cancer is one of the most prevalent and potentially life-threatening cancers globally, making it a critical area of focus in medical research. Early detection, followed by timely and appropriate treatment, can significantly enhance patient survival outcomes.

Study · 2026

NRLC-YOLO for lightweight detection and grasp positioning of latex cups in rubber plantations

Natural rubber harvesting remains highly dependent on manual labor, particularly during latex cup collection, which limits efficiency and increases operational costs. Intelligent robotic harvesting systems require accurate visual perception and reliable grasp point positioning under rubber plantation environments.

Study · 2026

Neural Controlled Differential Equation and Its Application in Pharmacokinetics and Pharmacodynamics

With the recent advances in machine learning (ML) and artificial intelligence (AI), data-driven modeling approaches for pharmacokinetics (PK) and pharmacodynamics (PD) have gained popularity due to their versatility in diverse settings and reduced reliance on prior assumptions.

Study · 2026

Optimized CNN-based ensemble deep learning approach for potato leaf disease detection with data augmentation

This paper explores the use of optimized convolutional neural networks (CNNs) to classify diseases affecting potato leaves using TensorFlow-2. The dataset, sourced from Kaggle's Plant Village repository, includes 152 images of healthy potato leaves and 1000 images each of early and late blight.

Study · 2026

Prediction of penicillin concentration using time series forecasting and machine learning techniques

Background Time-series forecasting is crucial in pharmaceutical fermentation, where early detection of deviations safeguards product quality.

Study · 2026

BrainFusionNet: a deep learning and XAI model to understand local, global, and sequential features of MRI images for improved brain tumour detection

The noise of Magnetic Resonance Imaging (MRI) poses challenges for Deep Learning (DL) when tumor boundaries are obscured, tumor location and appearance are complex due to overlap between tumor and non-tumor cells, and modality identification is difficult because tumor features vanish in the later layers of the DL.