Case Studies

Neglected Diseases

Drug Space

This ‘drug space’ was generated using StarDrop’s drug discovery chemical space visualisation using a set of 1395 marketed small molecule drugs. In this space, the proximity of two points represents the structural similarity between the corresponding compounds. This provides a convenient way to map the distribution of compounds or their properties across the chemical diversity of drugs. The figure below shows some illustrative structures for different regions of the space.

Technical Details

In generating this space, the similarity between two compounds is defined using a Tanimoto index based on a 2D path-based fingerprint. The distribution of points is generated using the t-distributed stochastic neighbour embedding algorithm [1].

Data Set

The compound structures used to create the drug space were downloaded from the ChEMBL approved drug list [2]. Only compounds assigned a ‘Development Phase’ of 4 were retained. Duplicate structures and compounds with molecular weight less than 100 Da or greater than 1000 Da were removed.

StarDrop users can download a Drug Space StarDrop Project containing this data set and plot their compounds into the same drug space.

Pharmacokinetics Scoring Profile

Each of the compounds were scored using StarDrop’s Probabilistic Scoring approach [3] for multi-parameter optimisation. This assesses the overall balance of properties against a profile of criteria representing the desired properties of a high quality compound for the therapeutic objectives of a project. The overall score, between 0 and 1, represents the likelihood of achieving the ideal outcome for all properties.

The ten drugs were scored based on their clinically observed pharmacokinetic (PK) properties:

  • Oral bioavailability (%)
  • Half-life (h)
  • Plasma-protein binding (%)
  • Volume of distribution (L)

For each compound, a histogram shows the performance of each of these properties against the desired property values, as illustrated right.

A high bar for a property indicates a good value of the property while a low bar corresponds to a poor value against an important property criterion. The data for each of the compounds, along with references to the sources, are provided in the table in the Data section below.

In some cases, a bar in a histogram is ‘greyed out’ indicating that the contribution of this compound is based on highly uncertain or missing data. For details, please see the table of detailed information for each compound below.

The scoring profile used to compare the ten compounds was as follows:

The range of desired values for each of the properties is shown above, along with the relative importance of each property criterion. However, the criteria are not defined as hard cut-offs, which could draw artificially harsh distinctions between compounds with similar property values near to the boundaries of the desired ranges. Instead, a ‘desirability function’ has been defined for each criterion, relating the value of each property to its desirability. The desirability functions used in this profile are shown below (in each case the desirability function is shown in blue and the histogram shows the distribution of the corresponding property values for the ten neglected diseases compounds):

1Only lowest 5 half-life compounds are shown on histogram for scale. Some compounds have half-life >100 hours.

This scoring profile is included in a Neglected Diseases StarDrop project which StarDrop users can download to score their own compounds, or modify as required.

The choice of a property profile is subjective to some degree, but the rationales for the choice of these desirability functions are as follows:

    • For an orally dosed compound, high oral bioavailability is desirable to achieve good systemic exposure. Typically, a value above 50% would be ideal, but below this, the higher the oral bioavailability the better. A value of zero is clearly unacceptable.
    • A half-life above 8 hours would be suitable for dosing no more frequently than twice-daily. A half-life below this would increase the likelihood of requiring larger number of doses or a larger dose to maintain a therapeutic concentration. Requiring a higher number of doses increases the risk of poor patient compliance while administration of large doses would require a high therapeutic index. Due to the challenges of supply and compliance in developing nations, less frequent dosing may be desirable and, in some cases, a single dose treatment would be ideal. Hence, longer half-lives are not penalised, despite the risk of accumulation, potentially leading to toxicity.
    • High plasma-protein binding reduces the free concentration of a compound; therefore, plasma-protein binding values close to 100% are undesirable. However, very low plasma-protein values are difficult to achieve; therefore, a desired range of less than 90% is defined.
    • A volume of distribution above 70L indicates distribution within total body water, hence a value greater than this would be desirable, with an ideal range between 210 L and 350 L, indicating good tissue exposure. A much higher volume of distribution indicates a greater degree of non-specific binding, increasing the risk of toxicity or undesirable pharmacology; therefore, values above 350L are assigned decreasing desirability, with values above 490 L given the lowest desirability.

Of course, there is no single ‘ideal’ pharmacokinetic profile for a drug for a neglected disease; there are variations in the preferred profile for specific diseases and there are certainly exceptions to these ‘rules’.

Drug Data

Name

First Discovered or Approved

Disease(s)

Estimated Number of people affected2
(k)

Daily Dose
(mg/70kg)

Oral bioavailability
(%)

Volume of distribution
(L)3

Plasma-protein binding
(%)

Half-life
(h)

Miltefosine

1980

Leishmaniasis

1,300

175

N/A 4

49 [4]

96-98 [4]

150-200 [5]

Posaconazole

2005

Antifungal

N/A

600

N/A 5

1774 [6]

>98 [6]

35 [6]

Suramin

1920

Trypanosomiasis and
Onchocerciasis

20

1,000

N/A6

20.6 [7]

99.7 [8]

864-1440 [8]

Clofazimine

1986

Leprosy

175

50

70 [9]

1470 [10]

High [11]

240 [9]

Bedaquiline

2012

Tuberculosis

10,400

400

N/A]

164 [12]

>99.9 [12]

3,500 [13]

Diethylcarbamazine

1947

Lymphatic Filariasis

120,000

420

80-85 [14]

200 [15]

Negligible [16]

8 [16 ]

Nifurtimox

1965

Chagas disease, Trypanosomiasis,
and Leishmaniasis

205,000

1,050

50-79 [17]

755 [18]

N/A

3 [18]

Mefloquine

1970

Malaria and Schistosomiasis

240,000

1,050

89 [19]

1,400 [20]

98 [20]

336-672 [20]

Praziquantel

1982

Schistosomiasis

258,000

2,800

Low [21]

8000 [22]

80-85 [22]

2 [21] [23]

Mebendazole

1971

Antihelmintic activity

1,500,000

500

2-22 [24] [25]

142.1 [24]

90-95 [26]

5.5 [26]

These data can be downloaded in a Neglected Diseases StarDrop Project along with the compound structures and scores.

2 According to the World Health Organisation or Wikipedia
3 Assuming a 70 kg patient
4 Not measured due to haemolysis (high in rats and dogs)
5 No IV formulation, therefore absolute bioavailability cannot be determined
6 Administered intravenously

References

1 van der Maaten LPJ, Hinton GE. Visualizing High-Dimensional Data Using t-SNE. Journal of Machine Learning Research. 2008;9:2579-2605.

2 European Bioinformatics Institute. ChEMBL Approved Drugs. [Internet]. [cited 2016 August 28]. Available from: https://www.ebi.ac.uk/chembl/.

3 Segall MD. Multi-Parameter Optimization: Identifying high quality compounds with a balance of properties. Curr. Pharm. Des. 2012;18(9):1292-1310.

4 DrugBank. Miltefosine. [Internet]. [cited 2017 February 8]. Available from: https://www.drugbank.ca/drugs/DB09031.

5 Dorlo TPC, Balasegaram M, Beijnen JH, de Vries PJ. Miltefosine: a review of its pharmacology and therapeutic efficacy in the treatment of leishmaniasis. J. Antimicrob. Chemother. 2012;66(11):2576-2597.

6 DrugBank. Posaconazole. [Internet]. [cited 2017 February 8]. Available from: https://www.drugbank.ca/drugs/DB01263.

7 Chijioke CP, Umeh RE, Mbah AU, Nwonu P, Fleckenstein LL, Okonkwo PO. Clinical pharmacokinetics of suramin in patients with onchocerciasis. Eur. J. Clin. Pharmacol. 1998;54(3):249-251.

8 DrugBank. Suramin. [Internet]. [cited 2017 February 8]. Available from: https://www.drugbank.ca/drugs/DB04786.

9 DrugBank. Clofazimine. [Internet]. [cited 2017 February 8]. Available from: https://www.drugbank.ca/drugs/DB00845.

10 Nix DE, Adam RD, Auclair B, Krueger TS, Godo PG, Peloquin CA. Pharmacokinetics and relative bioavailability of clofazimine in relation to food, orange juice and antacid. Tuberculosis (edinb). 2004;84(6):365-373.

11 Lakshminarayana SB, Huat TB, Ho PC, Manjunatha UH, Dartois V, Dick T, Rao SPS. Comprehensive physicochemical, pharmacokinetic and activity profiling of anti-TB agents. J. Antimicrob. Chemother. 2014;70(3):857-867.

12 DrugBank. Bedaquiline. [Internet]. [cited 2017 February 8]. Available from: https://www.drugbank.ca/drugs/DB08903.

13 van Heeswijk RPG, Dannemann B, Hoetelmans RMW. Bedaquiline: a review of human pharmacokinetics and drug–drug interactions. J. Antimicrob. Chemother. 2014;69(9):2310-2318.

14 World Health Organisation. Diethylcarbamazine Citrate 100 mg Tablets: Summary of Product Characteristics. [Internet]. [cited 2017 February 8]. Available from: https://extranet.who.int/prequal/sites/default/files/NT002part4v1.pdf.

15 Edwards G, Awadzi K, Breckenridge AM, Giles HM, Orme ML, S.A. W. Diethylcarbamazine disposition in patients with onchocerciasis. Clin. Pharmacol. Ther. 1981;30(5):551-554.

16 DrugBank. Diethylcarbamazine. [Internet]. [cited 2017 February 8]. Available from: https://www.drugbank.ca/drugs/DB00711.

17 Yoshida F, Topliss JG. QSAR Model for Drug Human Oral Bioavailability. J. Med. Chem. 2000;43(13):2575-2585.

18 Drugs.com. Nifurtimox. [Internet]. [cited 2017 February 8]. Available from: https://www.drugs.com/mmx/nifurtimox.html.

19 Looareesuwan S, White NJ, Warrell DA, Forgo I, Dubach UG, Ranalder UB, Schwartz DE. Studies of mefloquine bioavailability and kinetics using a stable isotope technique: A comparison of Thai patients with falciparum malaria and healthy caucasian volunteers. Br. J. Clin. Pharmac. 1987;24(1):37-42.

20 DrugBank. Mefloquine. [Internet]. [cited 2017 February 9]. Available from: https://www.drugbank.ca/drugs/DB00358.

21 Olliaro P, Delgado-Romero P, Keiser J. The little we know about the pharmacokinetics and pharmacodynamics of praziquantel (racemate and R-enantiomer). J. Antimicrob. Chemother. 2014;69(4):863-870.

22 DrugBank. Praziquantel. [Internet]. [cited 2017 February 9]. Available from: https://www.drugbank.ca/drugs/DB01058.

23 Antimicrobe.org. Praziquantel. [Internet]. [cited 2017 February 9]. Available from: http://www.antimicrobe.org/drugpopup/Praziquantel.htm.

24 Dawson M, Allan RJ, Watson TR. The pharmacokinetics and bioavailability of mebendazole in man: a pilot study using [3H]-mebendazole. Br. J. Clin. Pharmacol. 1982;14(3):453-455.

25 Dawson M, Braithwaite PA, Roberts MS, Watson TR. The pharmacokinetics and bioavailability of a tracer dose of [3H]-mebendazole in man. Br. J. Clin. Pharmacol. 1985;19(1):79-86.

26 DrugBank. Mebendazole. [Internet]. [cited 2017 February 9]. Available from: https://www.drugbank.ca/drugs/DB00643.