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What is alvaMolecule?

alvaMolecule is a no-code cheminformatics platform that enables users to visualize, curate, and standardize molecular datasets in preparation for analytical work. It supports widely-used molecular formats like SMILES and SDF/MOL2, allowing seamless navigation through collections in either grid or spreadsheet views while automatically importing pertinent data. The platform guarantees structure verification and standardization through built-in standardizers and customizable SMIRKS rules, aids in the detection and management of duplicates, and offers scaffold analysis to summarize essential frameworks. Moreover, it includes integrated filtering and charting features that enable sorting by substructures, calculated molecular descriptors, and various physicochemical properties. alvaMolecule can calculate approximately 88 structural and physicochemical properties, which include drug-like and lead-like scoring metrics such as LogP, TPSA, and the Lipinski alert index, ultimately supporting users in creating high-quality datasets for QSAR/QSPR modeling, descriptor computations, and virtual screening tasks. In addition, its intuitive interface makes it accessible for researchers of all coding skill levels, allowing them to effectively enhance their cheminformatics endeavors and streamline their research processes.

What is ACD/Labs Percepta Platform?

Percepta provides a comprehensive platform for calculating a range of physicochemical properties, as well as ADME characteristics and toxicity endpoints. Users can seamlessly analyze outcomes from its various calculators, with each module offering targeted information, features like structure highlighting, and specific calculation methods. Additionally, the platform includes robust filtering, sorting, and graphing functionalities, which facilitate the examination of predicted outcomes. To gauge the reliability of these predictions and their applicability to your current endeavors, you can utilize metrics such as reliability index, probability assessments, and comparisons with similar structures from established training sets. The data on calculated molecular properties can also be leveraged for studying structural modifications and optimizing leads to align with the desired product profile concerning absorption, distribution, metabolism, and excretion. Furthermore, incorporating experimental data can enhance your comprehension of the unique chemical landscape while simultaneously boosting the accuracy of predictions through integrated machine learning features. This multifaceted approach not only streamlines research but also fosters innovation in chemical property analysis.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Alvascience

Date Founded

2018

Company Location

Italy

Company Website

www.alvascience.com

Company Facts

Organization Name

Advanced Chemistry Development

Date Founded

1994

Company Location

Canada

Company Website

www.acdlabs.com/products/percepta/

Categories and Features

Categories and Features

Scientific Data Management System (SDMS)

Analytics
Artificial Intelligence (AI)
Audit
Centralized Data Repository
Collaboration
Compliance
Data Security
ELN Integration
LIMS Integration
Workflows

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