#EliLilly and #Insilico Medicine have signed a $2.75 billion deal to bring #AIdeveloped #drugs to the global market. The agreement includes upfront payments, milestone payments, and royalties, and builds on their existing collaboration.…

Eli Lilly Makes $2.75 Billion Bet on AI-Powered Drug Discovery Pharmaceutical titan Eli Lilly wants to bring medications developed with AI to market. To that end, the company has struck a $2.75 b...

#artificial #intelligence #AI #Eli #Lilly #Healthcare #Insilico […]

[Original post on pymnts.com]

Lilly puts up to $2.75bn into Insilico alliance Insilico has once again added to its roster of big pharma partners, signing a deal with Eli Lilly that includes a $115m upfront payment

AI specialist #Insilico has once again added to its roster of big pharma partners, signing a deal with #EliLilly that includes a $115m upfront payment.
pharmaphorum.com/news/lilly-p...

Eli Lilly reaches $2.75 billion deal with Insilico to bring AI-developed drugs to the global market - Replaye U.S. pharmaceutical giant Eli Lilly will give Hong Kong-listed Insilico $115 million upfront to bring some of its AI-discovered drugs to the global market.

Eli Lilly reaches $2.75 billion deal with Insilico to bring AI-developed drugs to the global market
replaye.com/eli-lilly-re...

#News #EliLilly #Insilico

InSilico-Lilly Deal Valued Up to $2.75bn InSilico and Eli Lilly announced a deal on Mar 29, 2026 worth up to $2.75bn; the headline cap exceeds typical AI-pharma collaborations and hinges on clinical translation.

InSilico-Lilly Deal Valued Up to $2.75bn: InSilico and Eli Lilly announced a deal on Mar 29, 2026 worth up to $2.75bn; the headline cap exceeds typical AI-pharma collaborations and hinges on clinical… 👈 Read full analysis #InSilico #EliLilly #PharmaPartnership #AIDrugDiscovery #ClinicalTranslation

Insilico Medicine and ASKA Pharmaceutical Team Up for Women's Health Innovations Insilico Medicine and ASKA Pharmaceutical have joined forces to explore new therapeutic targets for women's health issues, leveraging AI technology.

Insilico Medicine and ASKA Pharmaceutical Team Up for Women's Health Innovations #None #Cambridge #Women’s_Health #Insilico #ASKA

Extreme #geneticvariations in #propofol clearance could be easily compensated for in this #insilico analysis of #TCImodels

www.bjanaesthesia.org/article/S0007-0912(25)00...

VISI-ON-BRAIN Project (NAMs) - Creatio VISI-ON-BRAIN project is a Horizon Europe doctoral network advancing human-relevant neuroscience tools beyond animal models

We are proud to announc the launch of VISI-ON-BRAIN, a €4.5M #HorizonEurope #MSCA Doctoral Network coordinated by @Creatio

15 early-stage researchers will develop human #inVitro & #inSilico #NAMs beyond animal models.

👉 bit.ly/VISI-ON-BRAIN

@ub.edu @idibaps.bsky.social @ubneuro.bsky.social

Five key shared descriptors (P_VSA_LogP_5, R8s, ATS4m, Eta_betaS_A, BLTA96) captured hydrophobicity, topology, symmetry, and baseline toxicity, improving cross-species generalization under data-limited conditions.

#toxicity #Ecotoxicology #insilico #machinelearning #cheminformatics #QSAR

Recent developments in the #biopharma #AI world include an #alliance between #ThermoFisherScientific and #Datavant, plus news from #Insilico, #Evinova, #BPGbio, #Evogene, and #AMPLY.

buff.ly/2z49luQ

Software Solutions for Chemoinformatics and QSAR - Alvascience Software Solutions for Chemoinformatics and QSAR

📄 Read the full paper:
www.mdpi.com/1420-3049/31...

🔗 Learn more about Alvascience tools:
www.alvascience.com

#cheminformatics #machinelearning #insilico #chemsky

📢 26. - 30. January 2026 The Faculty of Science at Palacký Univerzity hosts the Advanced in silico Drug Design Workshop 2026 – a 5-day international event focused on modern computational approaches to drug discovery, including AI and hands-on training 🧬💻 #DrugDiscovery #Bioinformatics #InSilico #AI

"Awake, awake. This is a dream state"

#InSilico is a stealth-puzzle adventure where, after waking up from a simulation, you must escape reality. Add to your wishlist on Steam!
-
#gamedev #indiegame #videogames #indiedev

Figure 1 from the linked paper showing a ‘Schematic representation of in silico methods across the rare disease therapeutic pipeline.’ The caption reads: “Methods span from diagnosis (e.g., variant analysis) to drug discovery (e.g., virtual screening), preclinical development (e.g., disease modeling), and clinical trials (e.g., virtual patients, pharmacokinetics/ pharmacodynamics (PK/PD) modeling). Abbreviations: PBPK physiologically based pharmacokinetics, popPK population pharmacokinetics, HTS, high-throughput screening, QSAR quantitative structure–activity relationship.”

🖥️ #InSilico tech is revolutionizing #RareDisease research! 🦓

Computational models, machine learning, and digital twins can:
✅ Integrate complex data
✅ Simulate biology
✅ Predict actionable outcomes

#HumanRelevant 🧪 🧬

Insilico and Servier Strike Up to 888 Million Dollar AI Oncology Drug Discovery Deal - OncoDaily Insilico and Servier Strike Up to 888 Million Dollar AI Oncology Drug Discovery Deal / AI, AI and healthcare, biotech, cancer, Insilico, OncoDaily, OncoDaily

Insilico and Servier Strike Up to 888 Million Dollar AI Oncology Drug Discovery Deal

oncodaily.com/techology/in...

#OncoDaily #Oncology #Cancer #Health #Medicine #MedEd #MedOnc #MedNews #Insilico #Servier

Quantitative Structure–Activity Relationship Models for Ready Biodegradability of Chemicals The European REACH regulation requires information on ready biodegradation, which is a screening test to assess the biodegradability of chemicals. At the same time REACH encourages the use of alternatives to animal testing which includes predictions from quantitative structure–activity relationship (QSAR) models. The aim of this study was to build QSAR models to predict ready biodegradation of chemicals by using different modeling methods and types of molecular descriptors. Particular attention was given to data screening and validation procedures in order to build predictive models. Experimental values of 1055 chemicals were collected from the webpage of the National Institute of Technology and Evaluation of Japan (NITE): 837 and 218 molecules were used for calibration and testing purposes, respectively. In addition, models were further evaluated using an external validation set consisting of 670 molecules. Classification models were produced in order to discriminate biodegradable and nonbiodegradable chemicals by means of different mathematical methods: k nearest neighbors, partial least squares discriminant analysis, and support vector machines, as well as their consensus models. The proposed models and the derived consensus analysis demonstrated good classification performances with respect to already published QSAR models on biodegradation. Relationships between the molecular descriptors selected in each QSAR model and biodegradability were evaluated.

📊 Based on Mansouri, K., (2013). Quantitative Structure–Activity Relationship Models for Ready Biodegradability of Chemicals. Journal of Chemical Information and Modeling, 53(4), 867–878. doi.org/10.1021/ci40... via @pubs.acs.org

#insilico #toxicology #chemsky

alvaQSAR

Models:
🔹 Accuracy up to 0.87 on external test sets
🔹 Built-in Applicability Domain
🔹 Fully documented & free to use

Try it now: alvascience.com/alva/qsar/
More on alvaDesc: alvascience.com/alvadesc/

#alvaQSAR #QSAR #Cheminformatics #Biodegradability #REACH #InSilico #alvaDesc

LOVE the promise of increasing support for data-driven biology. There is SO much data out there waiting to be mined & correctly organized to spark discovery.

#sysbio #insilico

Intelligent consensus prediction for addressing ecotoxicological effects of diverse pesticides on California quail Birds occupy a major portion of the ecology and are considered a valuable species. In this modern era, the application of pesticides has increased and caused very severe harmful consequences to variou...

🦜 Predicting pesticide toxicity in birds
Samal et al. developed QSTR models using #alvaDesc descriptors to predict pesticide toxicity toward California quail.

🔗 Paper: doi.org/10.1039/D4EM...
🔗 alvaDesc: alvascience.com/alvadesc/

#QSAR #Cheminformatics #Ecotoxicology #InSilico #chemsky

This.

"...increasing genomic data alone does not guarantee impact – many genome assemblies remain fragmented, poorly annotated, and underutilized."

(Lempereur et al., 2025)

Progress in genomics still requires verification in a laboratory.

#genomics #insilico #invitro #invivo

Quantitative read-across structure–property relationship (q-RASPR): a novel approach to estimate the bioaccumulative potential for diverse classes of industrial chemicals in aquatic organisms The Bioconcentration Factor (BCF) is used to evaluate the bioaccumulation potential of chemical substances in reference organisms, and it directly correlates with ecotoxicity. Traditional in vivo BCF ...

📊 Based on Bhattacharyya et al., 2024 doi.org/10.1039/D4EM..., the model uses 978 molecules and 6 2D descriptors:
• X1A (branching ↓ logBCF)
• Cl-089, MLOGP (lipophilicity ↑ bioaccumulation)
• MaxsOH, MaxdO, B03[C–N] (H-bonding ↓ logBCF)

#Toxicology #PBT #InSilico

Fortunately, researchers are now turning to human-based science for #StrokeResearch:

🧬 #InSilico trials using virtual patients
🧫 Brain #organoids & vascularized tissues for real-time observation of human biology
💻 #Organ-chips & #3D printing to model complex brain systems & test drugs

🧠 In silico evidence is reshaping medical device regulation. Watch our seminar on a validated assessment pipeline for vagus nerve stimulation using o²S²PARC & SPARC data.
🎥 youtu.be/YB-OazJHWaw
Meet us at IEEE EMBS NER! neuro.embs.org/2025/%F0%9F%...
#InSilico #MedicalDevices #SPARC

New study in Results in Engineering uses #alvaDesc + ML to predict corrosion inhibition of phenyl phthalimide derivatives

ANN achieved R² > 0.9 using DFT- and MD-derived features.

📄 doi.org/10.1016/j.ri...
🔗 alvascience.com/alvadesc/

#Cheminformatics #MachineLearning #InSilico

Pandey & Roy (2025) apply read-across + ML to predict drug-induced cardiotoxicity using FDA DICTrank data 🧠

Descriptors from #alvaDesc enabled robust and interpretable models.

📄 doi.org/10.1016/j.in...
🔗 alvascience.com/alvadesc/

#QSAR #Cheminformatics #DrugSafety #InSilico #chemsky

🆕 #SysRev Findings ⤵️

Computational simulations have the potential improve accuracy, translation, and drug development, decreasing the risk of late-stage failure and advancing the promise of personalized medicine.

#insilico 🧪 🧬

alvaQSAR

Accessible in alvaQSAR, a free web platform offering predictive models for human health and environmental endpoints, each with detailed scientific documentation.

Try it out at: alvascience.com/alva/qsar/

#alvaQSAR #QSAR #Cheminformatics #Ecotoxicology #InSilico #ToxicityPrediction

Redirecting

Key features:
✅ Consensus modeling (ICP) improved predictivity
✅ Key features: electronegativity, lipophilicity, pyrroles, tertiary amines
✅ Descriptors from #alvaDesc www.alvascience.com/alvadesc/

#QSTR #toxicity #insilico #cheminformatics #3Rs

Il y a des projets auxquels j'ai participé et / ou donné mon avis professionnel qui ne décollent pas, et dont la dénomination se diffuse dans le "domaine public" : les clients potentiels ont des attentes non-dites...

#BioInformatique #InVivo #InVitro #InSilico #JumeauNumérique