improving the prediction of brain disposition for orally administered

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IMPROVING THE PREDICTION OF BRAIN DISPOSITION FOR ORALLY ADMINISTERED DRUGs USING BDDCS:

IMPROVING THE PREDICTION OF BRAIN DISPOSITION FOR ORALLY ADMINISTERED DRUGs USING BDDCS

CONTENTS:

CONTENTS Introduction Criteria for data collection Elaboration, analysis and application of rules for brain disposition prediction Conclusion References

INTODUCTION:

INTODUCTION Delivery of new drug candidates to the CNS is a challenging problem in drug development. It is important to design drugs that target the CNS when it is the site of action and also important to prevent peripherally acting drugs from accessing the CNS where they could exert undesirable and potentially harmful side effects .

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QSAR studies have been instrumental in early phases of drug discovery, serving as fast and inexpensive tools to prioritize new molecular entities (NMEs) as candidate CNS agents. BBB disposition has been linked to molecular properties such as drug lipophilicity ( LogP and LogD7.4) , molecular weight , and the tendency to form hydrogen bonds quantified as polar surface area (PSA) or as a function of nitrogen and oxygen counts. These approaches led to simple rules of thumb, or to more elaborate in silico models for predicting CNS disposition yielding ~80% accuracies for early phase screening.

BDDCS CLASIFICATION:

BDDCS CLASIFICATION The Biopharmaceutics Drug Disposition Classification System (BDDCS) has been successful in predicting in vivo absorption, disposition, and drug–drug interactions of marketed drug. BDDCS is a four class system based on extent of metabolism and solubility measures that has been used to explain the role of transporters in pharmacokinetics and their interplay with metabolizing enzymes in the liver and intestine.

CLASSIFICATION:

CLASSIFICATION CLASS-1 : High solubility, Extensive metabolism. CLASS-2 : Low solubility, Extensive metabolism. CLASS-3 : High solubility, Poor metabolism. CLASS-4 : Low solubility, P oor metabolism. Solubility class is defined based on the dose number (Do): Do = (HDS/250mL )/ LWS HDS is the highest dose strength approved for commercial use LWS is the lowest water solubility at 37 °C in the pH range from 1 to 7.5

CRITERIA FOR DATA COLLECTION:

CRITERIA FOR DATA COLLECTION In modeling blood–brain barrier (BBB) passage, in silico models have yielded ~80% prediction accuracy, and are currently used in early drug discovery. Being derived from molecular structural information only, these models do not take into account the biological factors responsible for the in vivo outcome. Passive permeability and P-glycoprotein ( Pgp , ABCB1) efflux have been successfully recognized to impact xenobiotic extrusion from the brain, as Pgp is known to play a role in limiting the BBB penetration of oral drugs in humans .

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Efflux ratio: The Pgp impact on drug permeability, evaluated in terms of efflux ratio (ER). ⟶a)/P 𝗮𝗽𝗽( a⟶b ) Papp( a→b ) - permeability from the apical to the basolateral side (absorption) Papp( b→a ) - permeability from the basolateral to the apical side (secretion).

ELABORATION, ANALYSIS AND APPLICATION OF RULES FOF BRAIN DISPOSITION:

ELABORATION, ANALYSIS AND APPLICATION OF RULES FOF BRAIN DISPOSITION Pgp and brain disposition: Of the 160 oral drugs for which Pgp ER data were available, 63 had more than one reported ER value in Borst cell lines. 87 % of these 63 drugs were classified coherently as either Pgp substrates or non-substrates.

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In silico permeability and brain disposition: Due to a lack of in vitro permeability data, we evaluated the relationship between in silico permeability and brain disposition by using the calculated octanol /water partition coefficient CLogP and the VolSurf + descriptor CACO2. LogP has been highly used in medicinal chemistry as a surrogate for permeability.

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List of oral drugs and data used for brain penetration prediction. Drug Pgp Substrate BDDCS Class Acebutolol + 1 Alprazolam − 1 Alprenolol − 1 Amantadine + 3 Amisulpride + 4 Amitriptyline − 1 Amoxapine − 1 Amprenavir + 2 Antipyrine − 1 Aprepitant + 2 Astemizole + 2 Atenolol − 3 Atomoxetine + 1 Biperiden − 1 Bromazepam − 1 Bromocriptine + 1 Bupropion − 1 Buspirone − 2

CONCLUSION::

CONCLUSION: Future prospects of BDDCS in drug discovery: Within the last decade, laboratory has investigated the relationship between drug transport and drug disposition in the human body , particularly with respect to transporter-enzyme interplay. The transformation of information into knowledge has been possible in part due to a simple four class system: the BDDCS. We recognized that classes 1, 2, and 3 have different profiles with respect to brain disposition , as well as protein binding , intestinal absorption, and potential drug–drug interactions.

REFERENCES::

REFERENCES: Advanced drug delivery reviews 64- (2012) C. Hansch , A.R. Steward, J. Iwasa , The correlation of localization rates of benzeneboronic acids in brain and tumor tissue with substituent constants, Mol. Pharmacol.1 (1965) 87–92.

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