will soon be adding papers on inverse design and QML It has a list of all the papers and blogs i have read on drug delivey and design

1)Materials of Drug Delivery -------------> 10%

http://sitn.hms.harvard.edu/flash/2011/materials-for-drug-delivery/

2)A Data-Driven Predictive Approach for Drug Delivery Using Machine Learning Techniques -----> 5%

https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0031724&type=printable

3)Deep learning forin vitroprediction ofpharmaceutical formulations ------>

https://reader.elsevier.com/reader/sd/pii/S221138351830282X?token=EB1B19BF77B4C8E9D40F60AD56AFCE7AD6762F0EA8F443E469B6CF60610F29C2FCD0C0C39987DC64ACE17CACB9A291A2

  A) Review of OFDF
  https://reader.elsevier.com/reader/sd/pii/S1319016415000626?token=92140C15A16116060052F611DA31FBEA849728ED7BD167DAC8AE7D56739A7900AA5AF8951452099EFE10A168FA6FE33A
  
  B) Review of Matrix Tablets
  
  http://jpsbr.com/index_htm_files/3_1151.pdf

4)‘‘Ant-Wall’’modeltostudydrugreleasefromexcipientmatrix ------------>

https://reader.elsevier.com/reader/sd/pii/S0378437118315425?token=9225F5AE241FB6D6C4CF2692E0055E7289CB2CE1AE938F9A1AAE9EF29A0856DBDE603ADC3BE9587E8EF676562BA472A3

5)Matrix Systems-----------> 100%

its a review paper , Mechanism of Drug Release, Effects and Properties, Kinetic of drug release

  a) Main Paper
  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3648939/

  b)http://jpsbr.com/index_htm_files/3_1151.pdf
    https://pdfs.semanticscholar.org/76bc/cd18e5072b6596a670bf456e9d5363af9fab.pdf
    https://www.idealcures.com/solutions/excipients_for_hydrophilic_matrix_tablets

6. Evaluating Intra-Articular Drug Delivery for the Treatment of Osteoarthritis in a Rat Model (Review Paper) 50% https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2817653/

https://reader.elsevier.com/reader/sd/pii/S1063458419309264?token=F4EE2A2EFFE5ADB495A0E641B6F5AEF7392A6F6FC318AE6AD55593EA2330BDB533AD4097AE74355A290A7856002934B0

7. tubercolosis a)https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3076728/ b)https://www.aiin.healthcare/topics/diagnostics/harvard-machine-learning-model-drug-resistant-tb c)https://www.biorxiv.org/content/biorxiv/early/2018/03/03/275628.full.pdf d)https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5312000/ e)https://www.ncbi.nlm.nih.gov/pubmed/28237034

f) first and second drugs https://www.intechopen.com/books/tuberculosis-current-issues-in-diagnosis-and-management/first-and-second-line-drugs-and-drug-resistance#targetText=First%2Dline%20antituberculosis%20drugs%2D%20Isoniazid,)%20and%20streptomycin%20(SM).&targetText=Fluoroquinolones%2D%20Ofloxacin%20(OFX)%2C,)%20and%20capreomycin%20(CAP). g)https://www.sciencedirect.com/science/article/pii/S1472979216302335?via%3Dihu b

Making a new change