Table 4 - uploaded by Elnaz Tamizi
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A quantitative structure toxicity relationship (QSTR) is proposed to correlate the toxicity of drugs on rat after intravenous administration. The computational descriptors of 319 drug molecules are calculated using HyperChem software and regressed against LD50 of drugs collected from the literature. Correlation coefficient (R), F value and average...
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Context 1
... example, LD 50 of benzyl benzoate in rat after oral administration is 1.7 mg/Kg (7) and 2800 mg/Kg (9). The PD between two experimentally reported data is equal to 164600 %. Table 4 shows some of different data for LD 50 of drugs in rat after intrave- nous administration. As a conclusion, a quantitative structure toxicity relationship (QSTR) was proposed to correlate toxicity of drugs on rat. ...
Citations
... The correct stereochemistry was established by utilizing the (±)-threo-ritalinic acid as the starting material (oral communication Noramco, Athens, GA, US). The oral LD 50 of MPH in the rat is 350 mg/kg (Sigma-Aldrich, 2012) whereas the IV LD 50 of MPH is 48 to 50 mg/kg (Matthey & Smith, 2006;Separham, Eghbal, Tamizi, & Jouyban, 2011). ...
... The correct stereochemistry was established by utilizing the (±)-threo-ritalinic acid as the starting material (oral communication Noramco, Athens, GA, US). The oral LD 50 of MPH in the rat is 350 mg/kg (Sigma-Aldrich, 2012) whereas the IV LD 50 of MPH is 48 to 50 mg/kg (Matthey & Smith, 2006;Separham, Eghbal, Tamizi, & Jouyban, 2011). ...
AbstrakProses penemuan dan pengembangan obat merupakan proses panjang yang memerlukan banyak waktu dan biaya. Ada banyak calon molekul obat yang gagal mencapai pasaran karena alasan toksisitasnya yang tinggi, sehingga harus dapat diidentifikasi sedini mungkin. Hubungan kuantitatif struktur toksisitas (HKST) merupakan salah satu metode in silico yang cukup tangguh untuk memprediksi toksisitas. HKST merupakan persamaan matematis yang dibentuk dari variabel data endpoint toksisitas seperti LD50 sebagai variabel terikat dan sejumlah deskriptor sebagai variable bebas yang dihitung dari senyawa-senyawa dalam training set. Persamaan HKST kemudian digunakan untuk memprediksi toksisitas senyawa baru.Kata kunci : toksisitas, hubungan kuantitatif struktur toksisitas (HKST)AbstractThe process of drug discovery and development is a long process that requires a lot of time and costly. There are many prospective drug molecules that fail to reach the market due to high toxicity reasons, so they must be identified as early as possible. The quantitative structure toxicity relationship (QSTR) is one of the in silico methods that is strong enough to predict toxicity. QSTR is a mathematical equation formed from endpoint toxicity data variables such as LD50 as a bound variable and a number of descriptors as independent variables calculated from the compounds in the training set. The QSTR equation is then used to predict the toxicity of new compounds.Keywords: toxicity, quantitative structure toxicity relationship (QSTR)
The nonmedical use of legal prescription drugs by healthy subjects has increased tremendously during the last decades, particularly in young people. The health concerns regarding potential addiction to these prescription drugs have created an increased awareness for both the pharma industry and governmental agencies worldwide toward more profound investigation of the abuse potential of all medicinal drug candidates in development (irrespective of their therapeutic indication) whenever they exert an activity in the brain.
The drug licensing authorities have therefore released distinct guidances on the investigation of the abuse potential of drug candidates and on the evaluation and labeling of abuse deterrent opioids.
Driven by these guidelines, the pharma industry is being coerced into taking increased responsibility to identify in more detail the abuse potential of new CNS-active drug candidates in development, primarily to protect the patient who will use this medication as prescribed, but also to prohibit, in every conceivable way, the possibility of abuse practices within the healthy population.
As such, an extensive Abuse Liability Assessment must be submitted to the regulatory agencies, consisting of preclinical investigations of the physical dependence and of the rewarding and reinforcing properties of new CNS-active drug candidates, but also including consequences at the clinical, regulatory, and final product form level and the subsequent scheduling as controlled substances (DEA).
This chapter provides resources on regulatory guidances worldwide and preclinical designs to study the abuse potential of novel drug candidates.
