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diff --git a/README.md b/README.md
@@ -23,9 +23,9 @@ The [CADD Vault](https://drugbud-suite.github.io/CADD_Vault/) includes resources
 - Machine Learning Applications in Drug Design
 - Fragment-Based Drug Design (FBDD)
 - Datasets for Drug Design
-Number of publications: 1128  
-Number of code repositories: 957  
-Number of webserver links: 150  
+Number of publications: 1146  
+Number of code repositories: 969  
+Number of webserver links: 161  
 Number of webserver links: 123  
 
 

diff --git a/cadd_vault_data.xlsx b/cadd_vault_data.xlsx
diff --git a/docs/ADMET/Pretrained Models.md b/docs/ADMET/Pretrained Models.md
@@ -5,7 +5,7 @@ icon: material/needle
 
 ## **BBB**
 - **BBB-score**: The Blood–Brain Barrier (BBB) Score  
-		[![Code](https://img.shields.io/github/stars/gkxiao/BBB-score?style=for-the-badge&logo=github)](https://github.com/gkxiao/BBB-score) [![Last Commit](https://img.shields.io/github/last-commit/gkxiao/BBB-score?style=for-the-badge&logo=github)](https://github.com/gkxiao/BBB-score) [![Publication](https://img.shields.io/badge/Publication-Citations:203-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1021/acs.jmedchem.9b01220) 
+		[![Code](https://img.shields.io/github/stars/gkxiao/BBB-score?style=for-the-badge&logo=github)](https://github.com/gkxiao/BBB-score) [![Last Commit](https://img.shields.io/github/last-commit/gkxiao/BBB-score?style=for-the-badge&logo=github)](https://github.com/gkxiao/BBB-score) [![Publication](https://img.shields.io/badge/Publication-Citations:204-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1021/acs.jmedchem.9b01220) 
 
 ## **CYP450**
 - **D-CyPre**: Tool for Accurately Predicting the Site of Metabolism of Human Cytochrome P450 Metabolism  
@@ -15,47 +15,61 @@ icon: material/needle
 
 ## **General**
 - **ADMET_XGBoost**: ADMETboost: a web server for accurate ADMET prediction  
-		[![Code](https://img.shields.io/github/stars/smu-tao-group/ADMET_XGBoost?style=for-the-badge&logo=github)](https://github.com/smu-tao-group/ADMET_XGBoost) [![Last Commit](https://img.shields.io/github/last-commit/smu-tao-group/ADMET_XGBoost?style=for-the-badge&logo=github)](https://github.com/smu-tao-group/ADMET_XGBoost) [![Publication](https://img.shields.io/badge/Publication-Citations:37-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1007/s00894-022-05373-8) 
+		[![Code](https://img.shields.io/github/stars/smu-tao-group/ADMET_XGBoost?style=for-the-badge&logo=github)](https://github.com/smu-tao-group/ADMET_XGBoost) [![Last Commit](https://img.shields.io/github/last-commit/smu-tao-group/ADMET_XGBoost?style=for-the-badge&logo=github)](https://github.com/smu-tao-group/ADMET_XGBoost) [![Publication](https://img.shields.io/badge/Publication-Citations:38-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1007/s00894-022-05373-8) 
 - **admet-ai**: ADMET-AI: A machine learning ADMET platform for evaluation of large-scale chemical libraries  
 		[![Code](https://img.shields.io/github/stars/swansonk14/admet_ai?style=for-the-badge&logo=github)](https://github.com/swansonk14/admet_ai) [![Last Commit](https://img.shields.io/github/last-commit/swansonk14/admet_ai?style=for-the-badge&logo=github)](https://github.com/swansonk14/admet_ai) [![Publication](https://img.shields.io/badge/Publication-Citations:16-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1093/bioinformatics/btae416) 
-- **ADMETlab**:   
+- **ADMETlab**: systematical evaluation of ADMET properties, as well as some physicochemical properties and medicinal chemistry friendliness  
 		[![Code](https://img.shields.io/github/stars/ifyoungnet/ADMETlab?style=for-the-badge&logo=github)](https://github.com/ifyoungnet/ADMETlab) [![Last Commit](https://img.shields.io/github/last-commit/ifyoungnet/ADMETlab?style=for-the-badge&logo=github)](https://github.com/ifyoungnet/ADMETlab) [![Publication](https://img.shields.io/badge/Publication-Citations:75-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1093/nar/gkae236) 
-- **ADMETlab3.0**:   
-	[![Publication](https://img.shields.io/badge/Publication-Citations:75-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1093/nar/gkae236) [![Link](https://img.shields.io/badge/Link-online-brightgreen?style=for-the-badge&logo=cachet&logoColor=65FF8F)](https://admetlab3.scbdd.com) 
+- **ADMETlab3.0**: systematical evaluation of ADMET properties, as well as some physicochemical properties and medicinal chemistry friendliness  
+	[![Publication](https://img.shields.io/badge/Publication-Citations:75-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1093/nar/gkae236) [![Link](https://img.shields.io/badge/Link-offline-red?style=for-the-badge&logo=xamarin&logoColor=red)](https://admetlab3.scbdd.com) 
 - **ChemMORT**: ChemMORT: an automatic ADMET optimization platform using deep learning and multi-objective particle swarm optimization  
 		[![Code](https://img.shields.io/github/stars/leelasd/ChemMORT?style=for-the-badge&logo=github)](https://github.com/leelasd/ChemMORT) [![Last Commit](https://img.shields.io/github/last-commit/leelasd/ChemMORT?style=for-the-badge&logo=github)](https://github.com/leelasd/ChemMORT) [![Publication](https://img.shields.io/badge/Publication-Citations:3-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1093/bib/bbae008) 
 - **Computation-ADME**:   
 		[![Code](https://img.shields.io/github/stars/molecularinformatics/Computational-ADME?style=for-the-badge&logo=github)](https://github.com/molecularinformatics/Computational-ADME) [![Last Commit](https://img.shields.io/github/last-commit/molecularinformatics/Computational-ADME?style=for-the-badge&logo=github)](https://github.com/molecularinformatics/Computational-ADME) [![Publication](https://img.shields.io/badge/Publication-Citations:21-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1021/acs.jcim.3c00160) 
 - **Datagrok Admetica**: Datagrok pretrained ADME models  
-		[![Code](https://img.shields.io/github/stars/datagrok-ai/admetica?style=for-the-badge&logo=github)](https://github.com/datagrok-ai/admetica) [![Last Commit](https://img.shields.io/github/last-commit/datagrok-ai/admetica?style=for-the-badge&logo=github)](https://github.com/datagrok-ai/admetica) [![Link](https://img.shields.io/badge/Link-online-brightgreen?style=for-the-badge&logo=cachet&logoColor=65FF8F)](https://public.datagrok.ai/browse/admetica.admeticaapp) 
+		[![Code](https://img.shields.io/github/stars/datagrok-ai/admetica?style=for-the-badge&logo=github)](https://github.com/datagrok-ai/admetica) [![Last Commit](https://img.shields.io/github/last-commit/datagrok-ai/admetica?style=for-the-badge&logo=github)](https://github.com/datagrok-ai/admetica) [![Link](https://img.shields.io/badge/Link-offline-red?style=for-the-badge&logo=xamarin&logoColor=red)](https://public.datagrok.ai/browse/admetica.admeticaapp) 
 - **QIP**: Machine learning model that predict the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of molecules.  
 		[![Code](https://img.shields.io/github/stars/standigm/qip?style=for-the-badge&logo=github)](https://github.com/standigm/qip) [![Last Commit](https://img.shields.io/github/last-commit/standigm/qip?style=for-the-badge&logo=github)](https://github.com/standigm/qip) [![Publication](https://img.shields.io/badge/Publication-Citations:0-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1021/acs.jcim.4c00772) 
+- **OPERA**:   
+		[![Code](https://img.shields.io/github/stars/NIEHS/OPERA?style=for-the-badge&logo=github)](https://github.com/NIEHS/OPERA) [![Last Commit](https://img.shields.io/github/last-commit/NIEHS/OPERA?style=for-the-badge&logo=github)](https://github.com/NIEHS/OPERA) [![Link](https://img.shields.io/badge/Link-offline-red?style=for-the-badge&logo=xamarin&logoColor=red)](https://ntp.niehs.nih.gov/whatwestudy/niceatm/comptox/ct-opera/opera.html) 
+- **VEGA**:   
+	[![Link](https://img.shields.io/badge/Link-offline-red?style=for-the-badge&logo=xamarin&logoColor=red)](https://www.vegahub.eu/portfolio-item/vega-qsar/) 
+- **SwissADME**: web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness  
+	[![Publication](https://img.shields.io/badge/Publication-Citations:N/A-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1038/srep42717) [![Webserver](https://img.shields.io/badge/Webserver-offline-red?style=for-the-badge&logo=xamarin&logoColor=red)](http://www.swissadme.ch/) 
+- **OCHEM**:   
+	[![Webserver](https://img.shields.io/badge/Webserver-offline-red?style=for-the-badge&logo=xamarin&logoColor=red)](https://ochem.eu/home/show.do) 
+- **vNN-ADMET**:   
+	[![Webserver](https://img.shields.io/badge/Webserver-offline-red?style=for-the-badge&logo=xamarin&logoColor=red)](https://vnnadmet.bhsai.org/vnnadmet/login.xhtml) 
 
 ## **Metabolites**
 - **MetaPredictor**: in silico prediction of drug metabolites based on deep language models  
 		[![Code](https://img.shields.io/github/stars/zhukeyun/Meta-Predictor?style=for-the-badge&logo=github)](https://github.com/zhukeyun/Meta-Predictor) [![Last Commit](https://img.shields.io/github/last-commit/zhukeyun/Meta-Predictor?style=for-the-badge&logo=github)](https://github.com/zhukeyun/Meta-Predictor) [![Publication](https://img.shields.io/badge/Publication-Citations:0-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1093/bib/bbae374) 
 
 ## **PK**
+- **Deep-PK**: deep learning for small molecule pharmacokinetic and toxicity prediction  
+	[![Link](https://img.shields.io/badge/Link-offline-red?style=for-the-badge&logo=xamarin&logoColor=red)](https://biosig.lab.uq.edu.au/deeppk/) 
+- **pkCSM**:   
+	[![Publication](https://img.shields.io/badge/Publication-Citations:N/A-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1021/acs.jmedchem.5b00104) [![Link](https://img.shields.io/badge/Link-online-brightgreen?style=for-the-badge&logo=cachet&logoColor=65FF8F)](https://biosig.lab.uq.edu.au/pkcsm/) 
 - **PKSmart**: This work used molecular structural fingerprints, physicochemical properties, and predicted animal PK data as features to model the human PK parameters VDss, CL, t½, fu and MRT for 1,283 unique compounds and developed a webhosted application **[PKSmart](https://pk-predictor.serve.scilifelab.se/)**, the first work that publicly releases PK models on par with industry-standard models.  
 		[![Code](https://img.shields.io/github/stars/srijitseal/PKSmart?style=for-the-badge&logo=github)](https://github.com/srijitseal/PKSmart) [![Last Commit](https://img.shields.io/github/last-commit/srijitseal/PKSmart?style=for-the-badge&logo=github)](https://github.com/srijitseal/PKSmart) [![Publication](https://img.shields.io/badge/Publication-Citations:7-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1101/2024.02.02.578658) 
 
 ## **Toxicity**
 - **ProTox3**: Webserver for toxicity prediction  
-	[![Publication](https://img.shields.io/badge/Publication-Citations:97-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1093/nar/gkae303) [![Webserver](https://img.shields.io/badge/Webserver-online-brightgreen?style=for-the-badge&logo=cachet&logoColor=65FF8F)](https://tox.charite.de/protox3/) 
+	[![Publication](https://img.shields.io/badge/Publication-Citations:106-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1093/nar/gkae303) [![Webserver](https://img.shields.io/badge/Webserver-offline-red?style=for-the-badge&logo=xamarin&logoColor=red)](https://tox.charite.de/protox3/) 
 ### **Toxicity**
 - **Cyto-Safe**: Webserver for toxicity prediction  
-		[![Code](https://img.shields.io/github/stars/LabMolUFG/cytosafe?style=for-the-badge&logo=github)](https://github.com/LabMolUFG/cytosafe) [![Last Commit](https://img.shields.io/github/last-commit/LabMolUFG/cytosafe?style=for-the-badge&logo=github)](https://github.com/LabMolUFG/cytosafe) [![Publication](https://img.shields.io/badge/Publication-Citations:0-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1021/acs.jcim.4c01811) [![Webserver](https://img.shields.io/badge/Webserver-online-brightgreen?style=for-the-badge&logo=cachet&logoColor=65FF8F)](http://insightai.labmol.com.br/) 
+		[![Code](https://img.shields.io/github/stars/LabMolUFG/cytosafe?style=for-the-badge&logo=github)](https://github.com/LabMolUFG/cytosafe) [![Last Commit](https://img.shields.io/github/last-commit/LabMolUFG/cytosafe?style=for-the-badge&logo=github)](https://github.com/LabMolUFG/cytosafe) [![Publication](https://img.shields.io/badge/Publication-Citations:0-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1021/acs.jcim.4c01811) [![Webserver](https://img.shields.io/badge/Webserver-offline-red?style=for-the-badge&logo=xamarin&logoColor=red)](http://insightai.labmol.com.br/) 
 
 ## **hERG**
 - **CardioTox**: A robust predictor for hERG channel blockade via deep learning meta ensembling approaches  
 		[![Code](https://img.shields.io/github/stars/Abdulk084/CardioTox?style=for-the-badge&logo=github)](https://github.com/Abdulk084/CardioTox) [![Last Commit](https://img.shields.io/github/last-commit/Abdulk084/CardioTox?style=for-the-badge&logo=github)](https://github.com/Abdulk084/CardioTox) [![Publication](https://img.shields.io/badge/Publication-Citations:30-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1186/s13321-021-00541-z) 
 - **CLOP-hERG**: Contrastive Learning Optimized Pretrained Model for Representation Learning in Predicting Drug-Induced hERG Channel Blockers  
 		[![Code](https://img.shields.io/github/stars/heshida01/CLOP-hERG?style=for-the-badge&logo=github)](https://github.com/heshida01/CLOP-hERG/blob/main/README.md) [![Last Commit](https://img.shields.io/github/last-commit/heshida01/CLOP-hERG?style=for-the-badge&logo=github)](https://github.com/heshida01/CLOP-hERG/blob/main/README.md) [![Publication](https://img.shields.io/badge/Publication-Citations:0-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.47852/bonviewMEDIN42022049) 
 - **hERGdb**: web-based cardiotoxicity prediction  
-	[![Publication](https://img.shields.io/badge/Publication-Citations:46-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1371/journal.pone.0199348) [![Webserver](https://img.shields.io/badge/Webserver-online-brightgreen?style=for-the-badge&logo=cachet&logoColor=65FF8F)](https://drugdesign.riken.jp/hERGdb/) 
+	[![Publication](https://img.shields.io/badge/Publication-Citations:46-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1371/journal.pone.0199348) [![Webserver](https://img.shields.io/badge/Webserver-offline-red?style=for-the-badge&logo=xamarin&logoColor=red)](https://drugdesign.riken.jp/hERGdb/) 
 
 ## **logP**
 - **OWPCP**: OWPCP: A Deep Learning Model to Predict Octanol-Water Partition Coefficient  
 		[![Code](https://img.shields.io/github/stars/jmohammadmaleki/OWPCP?style=for-the-badge&logo=github)](https://github.com/jmohammadmaleki/OWPCP.git) [![Last Commit](https://img.shields.io/github/last-commit/jmohammadmaleki/OWPCP?style=for-the-badge&logo=github)](https://github.com/jmohammadmaleki/OWPCP.git) [![Publication](https://img.shields.io/badge/Publication-Citations:0-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.48550/arXiv.2410.18118) 
 - **rescoss_logp_ml**: A repository dedicated to logP prediction using machine learning, offering insights into the solubility and distribution properties of compounds.  
-		[![Code](https://img.shields.io/github/stars/cisert/rescoss_logp_ml?style=for-the-badge&logo=github)](https://github.com/cisert/rescoss_logp_ml) [![Last Commit](https://img.shields.io/github/last-commit/cisert/rescoss_logp_ml?style=for-the-badge&logo=github)](https://github.com/cisert/rescoss_logp_ml) [![Publication](https://img.shields.io/badge/Publication-Citations:25-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1021/acsomega.2c05607) 
+		[![Code](https://img.shields.io/github/stars/cisert/rescoss_logp_ml?style=for-the-badge&logo=github)](https://github.com/cisert/rescoss_logp_ml) [![Last Commit](https://img.shields.io/github/last-commit/cisert/rescoss_logp_ml?style=for-the-badge&logo=github)](https://github.com/cisert/rescoss_logp_ml) [![Publication](https://img.shields.io/badge/Publication-Citations:26-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1021/acsomega.2c05607) 
diff --git a/docs/Bioinformatics/Sequence Family Classification.md b/docs/Bioinformatics/Sequence Family Classification.md
@@ -3,4 +3,4 @@ icon: material/crowd
 ---
 
 - **InterPro**: resource for the classification of protein sequences into families  
-	[![Publication](https://img.shields.io/badge/Publication-Citations:6-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1093/nar%2Fgkae1082) [![Webserver](https://img.shields.io/badge/Webserver-online-brightgreen?style=for-the-badge&logo=cachet&logoColor=65FF8F)](https://www.ebi.ac.uk/interpro) 
+	[![Publication](https://img.shields.io/badge/Publication-Citations:6-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1093/nar%2Fgkae1082) [![Webserver](https://img.shields.io/badge/Webserver-offline-red?style=for-the-badge&logo=xamarin&logoColor=red)](https://www.ebi.ac.uk/interpro) 
diff --git a/docs/CADD Challenges/CADD Challenges.md b/docs/CADD Challenges/CADD Challenges.md
@@ -0,0 +1,12 @@
+---
+icon: material/podium-gold
+---
+
+- **CACHE**: Critical Assessment of Computational Hit-Finding Experiments  
+	[![Link](https://img.shields.io/badge/Link-offline-red?style=for-the-badge&logo=xamarin&logoColor=red)](https://cache-challenge.org/) 
+- **CASF**: Comparative Assessment of Scoring Functions  
+	[![Publication](https://img.shields.io/badge/Publication-Citations:458-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1021/acs.jcim.8b00545) 
+- **CASP**: Critical Assessment of protein Structure Prediction  
+	[![Link](https://img.shields.io/badge/Link-offline-red?style=for-the-badge&logo=xamarin&logoColor=red)](https://predictioncenter.org/) 
+- **MAINFRAME**: Global Open Science Machine Learning Network for Drug Discovery  
+	[![Link](https://img.shields.io/badge/Link-offline-red?style=for-the-badge&logo=xamarin&logoColor=red)](https://aircheck.ai/mainframe) 
diff --git a/docs/Chemical Space/Chemical Space Comparison.md b/docs/Chemical Space/Chemical Space Comparison.md
@@ -3,4 +3,4 @@ icon: material/select-compare
 ---
 
 - **SpaceCompare**: Comparison of Combinatorial Fragment Spaces  
-	[![Publication](https://img.shields.io/badge/Publication-Citations:25-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1021/acs.jcim.1c01378) [![Link](https://img.shields.io/badge/Link-online-brightgreen?style=for-the-badge&logo=cachet&logoColor=65FF8F)](https://www.zbh.uni-hamburg.de/en/forschung/amd/software/spacecompare.html) 
+	[![Publication](https://img.shields.io/badge/Publication-Citations:25-blue?style=for-the-badge&logo=bookstack)](https://doi.org/10.1021/acs.jcim.1c01378) [![Link](https://img.shields.io/badge/Link-offline-red?style=for-the-badge&logo=xamarin&logoColor=red)](https://www.zbh.uni-hamburg.de/en/forschung/amd/software/spacecompare.html)