Reintroduction of generic drugs by second medical use patents also contributes to cheaper and faster drug development processes.
The PPARγ action of the selected generics was also investigated by in vitro and in vivo experiments.
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Materials and methods: The in silico oDPM method was used to determine the binding potency of 1, generics to proteins collected. Induction by nitazoxanide was higher than by bromfenac. Nitazoxanide lowered fasting blood glucose levels and improved insulin sensitivity in type 2 diabetic rats.
Conclusion: We demonstrated that the oDPM method can predict previously unknown therapeutic diabetes spectrum journal abbreviation of generic drugs. Nitazoxanide can be the prototype chemical structure of the new generation of insulin sensitizers. Non-commercial uses of the diabetes spectrum journal abbreviation are permitted without any further permission from Dove Medical Press Ltd, provided the work is properly attributed.
In general, it can be estimated that only one out of every 50— candidates that enter into the preclinical research phase will finally reach the market; the remaining candidates will be abandoned during the preclinical or clinical phase of the development process.
Kovács et al effective drugs in the near future. Theoretically, there are several possibilities to shorten the amount of time or decrease the total costs required for drug development. Every activity that can speed up the development process and reduce the time-to-market can bear significant advances. The reason for the high attrition rate among drug candidates originated from either their inefficacy at treating human pathological conditions or from its safety concerns, since the beneficial and adverse effects can occur over the long-lasting administration of drugs.
In addition, drug candidates are unpredictable based on the in vitro and in vivo test systems used to characterize the pharmacokinetic and pharmacodynamic properties of a drug candidate. During the last decade, the cost of drug development significantly increased in p arallel with increasingly more rigorous regulations.
This resulted in the intention to develop drug candidates that — beside their improved efficacy — are proven to be safe. This led to the quest of establishing new methodologies to bring significant improvements in the predictability of the therapeutic and adverse effect profile of drug candidates. One possible approach is to use molecular docking methods to study the interaction between the drugs and their molecular targets.
Another, less widespread approach is the application of the docking results as virtual affinity fingerprints and using them as an interaction pattern IP that describes the general interaction properties of a molecule. Here, the overall information contained in the pattern is used instead of the data that can be concluded from the individual interactions. Such a method is Drug Profile Matching DPMwhich aims to relate the medical effect profiles and target profiles of approximately 1, Food and Drug Administration FDA approved small-molecule drugs with their virtual affinity fingerprints diabetes spectrum journal abbreviation, a series of docking scores of the molecule against the ligand binding sites of a predefined set of proteins.
We found that there is a strong relationship between the medical effects studied and 77 target categories with the virtual affinity fingerprints of the drugs.
We showed that DPM outperformed conventional two-dimensional and three-dimensional structural similarity-based prediction approaches in almost all examined categories. Apart from the already known effects, previously unrevealed bioactivities medical effects, targets, and so on can also be predicted for the existing drugs by this method. Although there are growing numbers of type 2 diabetic patients, the available remedy for this disease is confined to a limited number of drug classes.
The most frequently prescribed medication for the treatment of type 2 diabetes is the group of thiazolidinediones. The aim of the present study was to investigate whether our in silico prediction method could be used for diabetes spectrum journal abbreviation generic drugs in order to find new therapeutic indications. To test our methodological approach, the FDA database containing 1, generic drugs was screened to predict their PPARγ activation propensities.
Then, the in silico selected drugs were tested diabetes spectrum journal abbreviation vitro using PPARγ receptor-expressing cell cultures to determine whether they are able to activate the PPARγ receptor. The experiments presented conform to European Community guiding principles for the care and use of laboratory animals.
One-dimensional DPM The selection of potential PPARγ antagonist candidates was performed using a simpler version of the recently introduced DPM — a systematic, pattern-based, bioactivity prediction method.
The main difference between DPM and one-dimensional DPM oDPM presented here Figure 1A is that the latter method applies a one-dimensional distance-like metric to compare the IPs that were considered as vectors in a multidimensional space, while DPM generates hyperplanes to separate active and inactive compounds in the multidimensional space. In our earlier work, we found that at least ten members are required for a group to reliably perform multivariate statistical methods of DPM;2 with under ten members, an alternative evaluation method is required, like oDPM.
Reference set Instead of using a medical effect database, a single-target focused reference set of eight molecules was applied. These known PPARγ antagonists were rosiglitazone, bexarotene, gemfibrozil, pioglitazone, alpha-linolenic acid, fenofibrate, bezafibrate, and clofibrate. IP similarity calculations A similarity coefficient d based on the angle enclosed by two IP vectors was used to create the IP similarity matrix. The IP vectors are determined by the docking scores as coordinates in a dimensional space created by the members of the protein set.
Neighbor-based bioactivity prediction Based on the IP similarity matrix, similarity lists were generated to each member of the reference set. Applying the cut-off submit your manuscript www. Drugs A and X are docked to the members of the protein set. Their respective IPs with color-coded energy values ranging from green to red [ie, from lower DS to higher DS values, respectively] are compared, and a pairwise similarity value is calculated.
Based on these values, similarity lists are created for each drug, containing the remaining set of molecules in a decreasing order of kezelése köröm gomba diabetes mellitus. B Summary of the effect prediction method using oDPM.
In the first step, similarity lists are created for each drug in the reference set containing eight compounds in this case and cut at a predefined IP distance value d.
Then, drugs appearing multiple times in the truncated lists are collected. The remaining drugs are predicted to possess the given effect. The maximum number of appearances was three.
The study was carried out on well plate, withcells per well. Every treatment was done in triplicate. Dovepress The cells were pretreated with phorbol myristate 13acetate, which makes the cells similar to macrophages and sensitizes their PPARγ response.
Animals and study design The experiments were carried out on 5-week-old male Wistar rats. The lighting was set to hour light and hour dark periods.
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Forty-eight animals were used throughout the study, and they were divided into three main groups. The first main group of Wistar rats served as healthy, vehicle-treated controls.
These rats served as the insulin-resistant, nondiabetic, vehicle treated group. In the first two main groups of rats, eight rats per group were used. The third main group of rats was divided into four subgroups with eight rats per subgroup. After an additional week, the animals showed stable fasting hyperglycemia. This animal model mimics the two characteristic features of type 2 diabetes. This type 2 diabetic animal model was originally established and validated by Reed et al.
Any process consists of several tasks, and there may be precedence constraints among them. In our paper we consider a special case, where the precedence constraints form short disjoint directed paths. This model occurs frequently in practice, but as far as we know it is considered very rarely in the literature.
Dose selection As our ultimate goal was to find a generic drug that could be reintroduced in new clinical indications, the important aspect of our drug development paradigm was that the drug could improve insulin sensitivity in similar or lower doses than previously used in animal studies, where the drug demonstrated its efficacy in the originally approved indication such as nitazoxanide as an antiprotozoal agent.
After a middle sagittal surgical incision on the ventral surface of the neck, the trachea was exposed and a polyethylene tube was introduced into it to allow spontaneous breathing of the animals.
Then, the left jugular vein and the left carotid artery were exposed and cleaned from the adhering connective tissues. Insulin and glucose were infused as separate lines of infusion through the two branches of the left jugular vein, while the arterial cannula served for blood pressure monitoring as well as to obtain blood samples 0.
The rate of glucose infusion was adjusted in order to maintain euglycemia 5.
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The blood glucose concentration was determined by means of a glucometer Accu-Chek®; submit your manuscript www. In order to determine the fasting and steady-state plasma levels of insulin, additional blood samples were collected 0. Accordingly, the insulin sensitivity of the peripheral tissues was characterized by the insulin sensitivity index ISIa measure of the amount of glucose taken up by peripheral tissues per unit of plasma insulin concentration.
For instance, if two drugs possess the same IP, but with different average docking scores, their d value will be small, suggesting a high level of similarity. On the other hand, a single diabetes spectrum journal abbreviation docking score can cause significant error in the distance measurement. This disadvantage is eliminated in DPM. The average area under the curve value of oDPM on effect groups with at least ten members is 0. A further 44 compounds diabetes spectrum journal abbreviation on the list twice, while drugs reached one appearance; all of them were discarded.
The IP distance value matrix of these ten compounds is displayed in Table 2. It is notable that the compounds are close to each other and seem to form a fairly coherent group that is similar to the reference set average IP distance values and standard errors for the reference set and the predicted set are 1.
Lubiprostone is the only compound that is distant from the others. Based on these results, no further refinement of the prediction could be performed; therefore, these ten compounds were piped to in vitro screening. The greater SD can explain the observed nonsignificant alteration. In this comparison, lubiprostone proved to be the most effective, showing an approximate 10 times elevation in the normalized mRNA expression level, while nitazoxanide, suprofen and bromfenac showed 7 times, 6 times and 3 times elevation, respectively Figure 3.
Drug Design, Development and Therapy In vivo study, determination of wholebody insulin sensitivity Based on the in vitro data and the available information regarding these generic drugs, we selected nitazoxanide for further study in order to determine its insulin sensitizing effect on type 2 diabetic rats. The effect of different treatment schedules on the glycemic control of different groups of rats has been summarized in Figure 4 and Table 3.
Animals held on a HFD became insulin resistant, but not diabetic at the end of the 3-week diet period.
Rats treated with intravenous STZ at the end of the second week of the HFD regimen showed not only decreased insulin sensitivity compared to diabetes spectrum journal abbreviation animals, but also marked fasting hyperglycemia ie, these rats became type 2 diabetic. Finally, no significant difference among the MCRI could be observed in either treatment groups.
In addition, no alteration in the resting mean arterial blood pressure was observed Figure 4 and Table 3. Discussion 1.
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Among these four generics, nitazoxanide was chosen to further study its putative PPARγ receptor agonist action by means of HEGC in a rodent model of type 2 diabetes in order to explore its insulin sensitizing property.
There have been several attempts made, trying to shorten the time-to-market as well as to decrease the amount of human and financial resources needed for the drug development process. In order to solve these above mentioned difficulties, the interest of the pharmaceutical industry has turned to the renewal of generics. Using drugs at the same or lower concentrations, as well as for similar treatment periods as were used in their original indications, several steps in the diabetes spectrum journal abbreviation process can be spared, such as conducting time-consuming and costly toxicity studies; an example of this kind of drug renewal was published previously.
Notes: Lubiprostone elicited the greatest induction in mRNA expression, but its effect was not dose-dependent. Suprofen and nitazoxanide evoked a similar increment in mRNA expression, but only nitazoxanide showed a dose-dependent relationship.
The effect of bromfenac was also dose-dependent, but it induced the smallest enhancement in mRNA expression. Abbreviation: mRNA, messenger ribonucleic acid. By screening the FDA-approved generics molecule database, our results supported the original assumption that the in silico oDPM methodology applied could facilitate the initial drug candidate selection if the molecular structure of the target protein is known.
Here we combined the advantages of the in silico oDPM method and generics-based drug development strategy.
The in silico oDPM method used allows us to select candidates from the molecule library within a relatively short time period. Using generics in new therapeutic indication could shorten the development process. On the other hand, the in silico prediction method has some limitations.