WO2006017892A1

WO2006017892A1 - Methods for improving cognitive functioning

Info

Publication number: WO2006017892A1
Application number: PCT/AU2005/001227
Authority: WO
Inventors: Carissa Maree Coulston; Christopher Charles Tennant; Michael Perdices
Original assignee: Northern Sydney And Central Coast Area Health Service
Priority date: 2004-08-16
Filing date: 2005-08-16
Publication date: 2006-02-23

Abstract

The present invention relates to methods for improving cognitive functioning in an individual suffering from a neuropsychiatric disorder associated with impaired cognitive functioning, the method comprising administering to the individual a therapeutically effective amount of cannabis, or at least one extract or constituent thereof, or administering to the individual a therapeutically effective amount of at least one agonist of a cannabinoid receptor.

Description

Methods for (Improving Cognitive Functioning Technical Field

The present invention relates to methods for improving cognitive functioning in individuals suffering from neuropsychiatric disorders. The present invention also relates to compositions suitable for use in these methods. The methods and compositions of the invention find particular application in the treatment of individuals with Schizophrenia, Schizoaffective Disorder, and related disorders.

Background of the Invention

Schizophrenia is a neuropsychiatric disorder affecting approximately 1% of the population worldwide. It is generally chronic in nature, characterised by a range of positive and negative symptoms, neuroanatomical abnormalities, and most predominantly, neurotransmitter dysfunctions.

The positive symptoms of Schizophrenia include hallucinations and delusions (commonly referred to as "psychosis" or "psychotic symptoms"), disorganised/bizarre behaviours, and thought disorder. The negative symptoms include deficits in productivity and quality of speech (alogia), restricted emotional expression/feeling (affective flattening), reduced motivation and initiation (avolition/apathy), and withdrawal from socialisation and recreational activities (anhedonia/asociality),

Another hallmark feature of Schizophrenia is cognitive impairment. The majority of sufferers display reduced cognitive abilities as evidenced, for example, by deficits in attention and processing speed, executive functions, memory, perceptual abilities, and motor skills (see, for example, Seaton et al, 2001, Neuropsychology Review 11 : 45-66). Cognitive impairments have been extensively reported not only among individuals with

Schizophrenia, but also among alcohol and illicit substance users. Much less is known, however, about the associations between cognition and "dual diagnosis" (that is, Schizophrenia combined with substance use), as mental illness is generally excluded as a confounding factor in substance use research, and conversely, substance use is generally excluded as a confounding factor in Schizophrenia research.

Accordingly, there is a need for more rigorous assessment of the correlations between Schizophrenia and illicit substance (drug) use, and in particular, between cognitive functioning and illicit substance use in Schizophrenia.

Cannabis is the most commonly used and abused illicit drug among Schizophrenia sufferers (see for example Kavanagh ei al, 2004, Schizophrenia Research 66:115-124). Indeed, the rates of cannabis use among people with Schizophrenia are higher than in the general population (see for example Arseneault et al, 2004, British Journal of Psychiatry 184:110-117). Cannabis is generally considered to exert only a detrimental impact on Schizophrenia, by exacerbating positive symptoms. One of the neurotransmitter pathways by which cannabis is believed to exacerbate the positive symptoms of Schizophrenia is via activation of dopamine release in the mesolimbic system (Gessa et al., 1998, European Journal of Pharmacology 341 : 39-44). To date, only two studies have specifically investigated cannabis use and cognition in the Schizophrenia Spectrum Disorders (Liraud & Verdoux, 2002, Encephale 28:160-168; Pencer & Addington, 2003, Journal of Psychiatry and Neuroscisnce 28:48-54). In both studies, little evidence was found to suggest a correlation between cognitive performance and cannabis use. Indeed, after statistically controlling for the effects of confounding variables, the only correlations observed were negative, indicating poorer cognitive performance among Schizophrenia cannabis users.

The present inventors have found that when frequent long-term cannabis use is evaluated in the context of rigorously controlling a wide range- of potential confounding variables, significant positive associations between cannabis use and cognitive performance are identified, indicating an enhancing effect of cannabis on cognition in Schizophrenia.

Summary of the Invention

In a first aspect the present invention provides a method for improving cognitive functioning in an individual suffering from a neuropsychiatric disorder associated with impaired cognitive functioning, the method comprising administering to the individual a therapeutically effective amount of cannabis, or at least one extract or constituent thereof.

In a preferred embodiment the neuropsychiatric disorder is Schizophrenia, Schizoaffective Disorder, or a related disorder.

Improvement in cognitive functioning may be reflected in improvements in one or more aspects of cognition. The cognitive aspect may be selected from attention and processing speed, executive functions, memory, perceptual organisation, motor skills, and emotional processing.

The at least one cannabis constituent may be a cannabinoid or a cannflavin. The cannabinoid may be selected from the group consisting of: cannabidiol; Δ-9-tetrahydrocannabinol; Δ-8- tetrahydrocannabinol; cannabigerol; cannabichromene; cannabicycol; cannabielsoin; cannabinol; cannabinodiol; tetrahydrocannabinovarin; cannabidivarin; cannabidivarol; cannabinolic acid; olivetol; and cannabitriol. The cannflavin may be selected from cannflavin A or cannflavin B.

The constituent may be a natural constituent of cannabis or a synthetic constituent, including an analogue of a natural constituent. In particular embodiments, the synthetic cannabinoid may be nabilone, dronabinol, levonantradol, BRL-4664, synhexyl or other suitable cannabinoid analogue.

The method may comprise the administration of two or more cannabis constituents in a ratio sufficient to produce^' an improvement in cognitive functioning of the individual.

In a second aspect the present invention provides a method for improving cognitive functioning in an individual suffering from a neuropsychiatric disorder associated with impaired cognitive functioning, the method comprising administering to the individual a therapeutically effective amount of at least one agonist of a cannabinoid receptor. The cannabinoid receptor may be selected from, but is not limited to, the CB1 receptor and the

CB2 receptor. In a third aspect the present invention provides a pharmaceutical composition for improving cognitive functioning in an individual suffering from a neuropsychiatric disorder associated with impaired cognitive functioning, the composition comprising cannabis, or at least one extract or constituent thereof.

In a fourth aspect the present invention provides a pharmaceutical composition for improving cognitive functioning in an individual suffering from a neuropsychiatric disorder associated with impaired cognitive functioning, the composition comprising at least one agonist of a cannabinoid receptor.

The composition of the third or fourth aspect may further comprise one or more pharmaceutically acceptable diluents, excipients and/or adjuvants.

Pharmaceutical compositions of the present invention may comprise two or more cannabis constituents. The two or more cannabis constituents may be in a ratio sufficient to produce an improvement in cognitive functioning when administered to an individual suffering from a neuropsychiatric disorder associated with impaired cognitive functioning.

In a fifth aspect the present invention provides the use of an effective amount of cannabis, or at least one extract or constituent thereof for the manufacture of a medicament for improving cognitive functioning in an individual suffering from a neuropsychiatric disorder associated with impaired cognitive functioning.

In a sixth aspect the present invention provides the use of an effective amount of at least one agonist of a cannabinoid receptor for the manufacture of a medicament for improving cognitive functioning in an individual suffering from a neuropsychiatric disorder associated with impaired cognitive functioning.

Definitions

The term "neuropsychiatric disorder" as used herein refers to a condition which may be principally characterised by abnormalities of neurological activity, including dysfunction of neurotransmitter systems such that a symptom of the disorder is an impairment of cognition or cognitive functioning. Individuals may be diagnosed as suffering from such a "neuropsychiatric disorder" according to criteria of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV: American Psychiatric Association, 1995) and International Classification of Diseases (ICD-10: World Health Organisation, 1992). Exemplary neuropsychiatric disorders include, but are not limited to, Schizophrenia, Schizoaffective Disorder, and related disorders. The terms "cognitive functioning" and "neuropsychological functioning" as used herein refer to the cognitive abilities and performance of an individual as measured by various cognitive assessment tests known to those of skill in the art. Cognitive functioning may be measured by an individual's performance in aspects of cognition including, but not limited to, attention and processing speed, executive functions, memory, perceptual organisation, motor skills, and emotional processing. The terms "attention" and "processing speed" as used herein refer to those aspects of cognitive functioning including, but not limited to reaction time, immediate attention span, sustained attention and concentration, working memory, selective attention, and divided attention. The term "executive functions" as used herein refer to those aspects of higher order brain processes essential for maintenance of complex goal-directed behaviour and problem solving, including, but not limited to strategic planning and organisation, cognitive flexibility, abstract reasoning and conceptualisation, set-shifting, response regulation, self-monitoring, utilising error feedback, decision making, inhibition, and adaptability.

The term "memory" as used herein refers to those aspects of cognitive functioning including, but not limited to span of immediate retention and recall, learning and acquisition, effects of retroactive and proactive interference, and storage/encoding of information in long-term memory.

The term "perceptual organisation" as used herein refers to those aspects of cognition including, but not limited to the ability to interpret and make sense of information which is degraded or distorted from reality, typically presented in a format which increases the difficulty in recognising the information (e.g., pictures of animals and objects that have fragments missing; profiles of objects and animals that appear at angular rotations from the familiar lateral view, thereby masking key features needed to assist in recognising them). The term "improving" as used herein in the context of "cognitive functioning" means improving or enhancing the level of cognitive functioning in an individual compared to the normal or baseline level of cognitive functioning experienced by that individual in the absence of treatment according to the present invention. That is, "improving" refers to any improvement in one or more of the symptoms of cognitive impairment suffered by the individual. Improvements and enhancements in cognitive functioning may be quantitatively measured using any one or more cognitive assessment tests known to those of skill in the art and such improvement or enhancement may be short term (approximately for the duration of the treatment) or long term (sustained improvement for greater than the duration of the treatment).

As used herein, the term "therapeutically effective amount" includes within its meaning a sufficient amount of cannabis, an extract, constituent, or analogue thereof to provide the desired therapeutic effect. The exact amount required will vary from individual to individual depending on factors such as the age and general condition of the individual being treated, the severity of the disorder, the particular agent or compound being administered, the mode of administration, and so forth. Thus, it is not possible to specify an exact "effective amount". However, for any given case, an appropriate "effective amount" may be determined by one of ordinary skill in the art using only routine experimentation. The term "constituent" as used herein in the context of a constituent of cannabis refers to natural and synthetic cannabis constituents and analogues thereof, and to precursors, metabolites, derivatives of these constituents, and to analogues thereof. The term "constituent" also includes within its scope prodrugs and pharmaceutically acceptable salts of the above. A suitable metabolite or derivative may be a bioactive compound formed by the biochemical breakdown of a cannabis constituent. The term "analogue" as used herein means any variant of a cannabis constituent, which is structurally similar to the constituent but varies at one or more positions therefrom. Analogues include, but are not limited to alkyl analogues, such as propyl and methyl analogues. In the context of this specification, the term "comprising" means "including principally, but not necessarily solely". Furthermore, variations of the word "comprising", such as "comprise" and "comprises", have correspondingly varied meanings.

Brief Description of the Drawings

Embodiments of the invention will be described, by way of example only, with reference to the accompanying drawing:

Figure 1 graphs the number of cognitive components distinguishing performance between frequency of cannabis use subgroups by logistic regression analyses.

Cannabis is a commonly used recreational drug in many societies, and is known to induce a number of behavioural and psychological effects. Various parts of cannabis plants, extracts of these plants, and a number of their constituents have also been found to have beneficial therapeutic effects, for example, as anti-convulsants, anti-inflammatory agents, analgesics, and appetite stimulants.

The present invention is predicated on the surprising findings disclosed herein that a positive correlation exists between cannabis use and cognitive functioning among individuals suffering from Schizophrenia, a neuropsychiatric disorder associated with cognitive impairment.

As disclosed herein, analyses of neuropsychological performance demonstrated that with respect to frequency of cannabis use among Schizophrenia sufferers, high frequency cannabis use over a period of at least one year was associated with better cognitive performance than both medium and nil/low frequency cannabis use, and was not associated with worse cognitive functioning on any of the measures which distinguished performance between the frequency subgroups. Those aspects of cognitive functioning on which high frequency cannabis users performed better than medium and low frequency users were in the domains of attention and processing speed, executive functions, and perceptual organisation. Recency of cannabis use and lifetime cannabis abuse/dependence were other indices of cannabis use measured in the research described herein, however, cognitive performance did not substantially differentiate between users and non-users when frequency of use was controlled, demonstrating that frequency of cannabis use is a stronger predictor of neuropsychological performance than either recency of use or a lifetime history of abuse/dependence. Accordingly, a first aspect of the present invention provides a method for improving cognitive functioning in an individual suffering from a neuropsychiatric disorder associated with impaired cognitive functioning, the method comprising administering to the individual a therapeutically effective amount of cannabis, or at least one extract or constituent thereof.

The present invention further provides pharmaceutical compositions comprising cannabis, or at least one extract or constituent thereof for use in improving cognitive functioning in an individual suffering from a neuropsychiatric disorder associated with impaired cognitive functioning. Cannabis and extracts, constituents and analogues thereof

Whole cannabis plant material or extracts thereof (including crude extracts of leaves, and/or buds or flowers for example), may be utilised in the methods and compositions of the present invention. Cannabis plant material and extracts thereof may be in any form suitable for administration according to the methods of the invention, including as dried material. Suitable cannabis species may include Cannabis sativa, C. Mica and C. ruderalis and any hybrids thereof. Cannabis plants may be selected or cultivated under appropriate conditions according to the desired constituent(s). Alternatively, cannabis plants may be modified, for example genetically modified, so as to alter the relative concentrations of the constituents present. The principal chemical constituents that are unique to cannabis plants are termed cannabinoids.

More than 60 different cannabinoids have been identified to date. Although the relative ratios of cannabinoids vary in different plants and in different preparations, the predominant cannabinoids typically include tetrahydrocannabinols (Δ-9-tetrahydrocannabinol and Δ-8-tetrahydrocannabinol), cannabidiol and cannabinol. Δ-9-tetrahydrocannabinol is the cannabinoid primarily responsible for the psychoactive effects of cannabis and cannabis extracts. Effects of tetrahydrocannabinol include euphoria, altered spacial and temporal perception and appetite stimulation. The predominant non-psychotropic cannabinoid present in most cannabis plants and preparations is cannabidiol. Cannabidiol has little psychoactive effect, but has been shown to be capable of modifying at least some of the effects of Δ-9- tetrahydrocannabinol. Cannabis plants also contain prenylated fiavone compounds related to cannabinoids known as cannflavins, including, for example the non-psychoactive cannflavin A and cannflavin B.

Cannabis constituents for use in the methods and compositions of the present invention may be any cannabinoid or cannflavin. For example a cannabinoid may be selected from the following: cannabidiol; Δ-9-tetrahydrocannabinol; Δ-8-tetrahydrocannabinol; cannabigerol; cannabichromene; cannabicycol; cannabielsoin; cannabinol; cannabinodiol; tetrahydrocannabinovarin; cannabidivarin; cannabadivarol; cannabinolic acid; olivetol; and cannabitriol. As noted above, the term "constituent" includes within its scope precursors, metabolites, derivatives and analogues of cannabis constituents.

The cannabis constituents may be natural chemical constituents isolated from cannabis plants, plant material or extracts. One such whole plant cannabis extract known in the art is Sativex^® (GW Pharmaceuticals). Suitable methods for the extraction and isolation of natural cannabis constituents and their precursors, metabolites and derivatives are known to those skilled in the art. For example, US Patent No. 6,403,126 (Webster et a/.; issued 11 June 2002) and US published Patent Application No. 20030017216 (Schmidt et a/.; filed 23 July 2001), the disclosures of which are incorporated herein by reference, describe methods of preparing cannabis extracts and isolating cannabis constituents from various forms of cannabis plant material.

Alternatively, the cannabis constituents may be synthetically produced. A number of synthetic cannabinoid analogues have been produced, with similar structural characteristics to natural cannabinoids. Such synthetic compounds may have similar or altered properties with respect to their natural counterparts. Examples, not intended to limit the present invention in any way, include the synthetic tetrahydrocannabinol dronabinol (Marinol^®; UniMed Pharmaceuticals) and the dronabinol analogue nabilone (Cesamet^®; EIi Lilly & Co). Other synthetic tetrahydrocannabinol analogues include levonantradol, BRL-4664 and synhexyl.

Several synthetic cannabinoids such as the above synthetic tetrahydrocannabinols have been trialed and/or have been approved and employed clinically for treating a variety of conditions. For example dronabinol and nabilone are prescribed for treating nausea and vomiting in cancer patients undergoing chemotherapy. Dronabinol is also prescribed for use in combating loss of appetite and weight loss in HIV-positive patients. Pharmacological properties of a number of synthetic cannabinoids have been extensively studied (see for example Kumar et a/., 2001, Anaesthesia 56: 1059-1068 and, in relation to nabilone specifically, Ward and Holmes, 1985, Drugs 30: 127-144).

Methods of synthesizing cannabinoids are known to those skilled in the art. For example, US Patent No. 6,531,636 (Mechoulam et a/.; issued 11 March 2003; the disclosure of which is incorporated herein by reference), describes methods of chemically synthesising analogues of endogenous cannabinoids. Cannabis, and extracts and constituents thereof may be administered to an individual in accordance with the present invention either alone in combination with other therapies for the treatment of the neuropsychiatry disorder suffered by the individual. For such combination therapies, each component of the combination therapy may be administered at the same time, or sequentially in any order, or at different times, so as to provide the desired therapeutic effect. Alternatively, the components may be formulated together in a single dosage unit as a combination product. Cannabinoid receptor agonists

Cannabinoids exert their physiological effects in animals by binding to and activating specific cell surface receptors. To date, at least two subtypes of cannabinoid receptors, designated CB1 and CB2, have been identified in humans and other animals. Although the precise mechanism by which the effects of cannabinoids are mediated via these receptors, CB 1 and CB2 are members of the G protein coupled receptor superfamily and have been shown to inhibit adenylate cyclase activity and thus reduce cAMP levels. The expression patterns of CB1 and CB2 differ, with CB1 appearing to be almost exclusively expressed in the brain and central nervous system, and CB2 expressed peripherally, predominantly in the spleen (see Howlett et a/., 2002, Pharmacological Reviews 54:161-202), In addition to cannabinoids, several endogenous cannabinoid-like compounds have also been identified and shown to be agonists of cannabinoid receptors. For example the eicosanoid derivative anandamide is a potent agonist of the CB1 receptor. Other endogenous cannabinoid-like compounds include virodhamine, noladin ether and 2-arachidonyl glycerol (reviewed in Felder & Glass, 1998, Annual Review of Pharmacology and Toxicology 38:179-200, the disclosure of which is incorporated herein by reference).

Those skilled in the art will appreciate that the methods and compositions of the present invention need not be limited to cannabis, cannabis extracts and cannabis constituents. Rather, known and novel compounds that act as agonists of cannabinoid receptors, such as CB1 and CB2; are also contemplated. Such agonists may be selective in activating only one specific cannabinoid receptor type or may act on more than one cannabinoid receptor type. Pharmaceutical compositions

According to the present invention cannabis, extracts and constituents thereof or other substances

5 that act as agonists or partial agonists of cannabinoid receptors may be administered as pharmaceutical compositions which, when administered to an individual suffering from a neuropsychiatry disorder associated with impaired cognitive functioning, are capable of providing an improvement in cognitive functioning in the individual.

Compositions of the present invention are administered to individuals suffering from a o neuropsychiatric disorder associated with impaired cognitive functioning, in an amount sufficient to improve the cognitive functioning of the individual compared to the level of cognitive functioning of the individual in the absence of the composition. The composition should provide a quantity of the cannabis, extract(s) or constituent(s) sufficient to effectively treat the individual accordingly. The therapeutically effective dose level for any particular individual will depend upon a variety of factors including: the s specific neuropsychiatric disorder suffered by the individual and the severity of the disorder; activity of the cannabis, extract(s) or constituent(s) employed; the composition employed; the age, body weight, general health, sex and diet of the individual; the time of administration; the route of administration; the rate of sequestration of the cannabis, extract(s) or constituent(s); the duration of the treatment; drugs used in combination or coincidental with the treatment, together with other related factors well known in o medicine.

One skilled in the art would be able to determine, by routine experimentation, an effective, non¬ toxic amount of cannabis, extract(s) or constituent(s), or other substance acting as an agonist or partial agonist of a cannabinoid receptor which would be required to improve the cognitive functioning of specific individuals. ₅ Generally, an effective dosage is expected to be in the range of about 0.0001 mg to about IOOOmg per kg body weight per 24 hours; about 0.001 mg to about 750mg per kg body weight per 24 hours; about 0.01 mg to about 500mg per kg body weight per 24 hours; about 0.1 mg to about 500mg per kg body weight per 24 hours; about 0.1 mg to about 250mg per kg body weight per 24 hours; or about 1.Omg to about 250mg per kg body weight per 24 hours. 0 It will also be apparent to one of ordinary skill in the art that the optimal course of administration, such as, the number of doses of the composition given per day for a defined number of days, can be ascertained by those skilled in the art using conventional course of treatment determination tests.

In general, suitable compositions may be prepared according to methods which are known to those of ordinary skill in the art and accordingly may include a pharmaceutically acceptable carrier, 5 diluent and/or adjuvant.

Chemical constituents of cannabis are typically lipophilic and are often extracted in the form of oils. Various methods and compositions for increasing the bioavailability of lipophilic compounds are known to those of skill in the art and may be utilised in conjunction with the cannabis extracts and constituents in the methods and compositions of the present invention. The carriers, diluents and adjuvants must be "acceptable" in terms of being compatible with the other ingredients of the composition, and not deleterious to the recipient thereof. Examples of pharmaceutically acceptable carriers or diluents are demineralised or distilled water; saline solution; vegetable based oils such as peanut oil, safflower oil, olive oil, cottonseed oil, maize oil, sesame oils such as peanut oil, safflower oil, olive oil, cottonseed oil, maize oil, sesame oil, arachis oil or coconut oil; silicone oils, including polysiloxanes, such as methyl polysiloxane, phenyl polysiloxane and methylphenyl polysolpoxane; volatile silicones; mineral oils such as liquid paraffin, soft paraffin or squalane; cellulose derivatives such as methyl cellulose, ethyl cellulose, carboxymethylcβllulose, sodium carboxymethylcellulose or hydroxypropylmethylcellulose; lower alkanols, for example ethanol or iso- propanol; lower aralkanols; lower polyalkylene glycols or lower alkylene glycols, for example polyethylene glycol, polypropylene glycol, ethylene glycol, propylene glycol, 1,3-butylene glycol or glycerin; fatty acid esters such as isopropyl palmitate, isopropyl myristate or ethyl oleate; polyvinylpyrridone; agar; carrageenan; gum tragacanth or gum acacia, and petroleum jelly. For example, Marinol^® (dronabinol) is a synthetic tetrahydrocannabinol dissolved in sesame oil and produced in capsules of 2.5 mg, 5 mg and 10 mg. Similarly, nabilone is typically prepared in capsule form suitable for oral administration. Typically, the carrier or carriers will form from 10% to 99.9% by weight of the compositions.

Compositions of the present invention may be in any suitable form for administration by suitable routes, including oral, topical, nasal, and parenteral (intravenous, intra-arterial, intramuscular and subcutaneous) routes. As noted above, cannabis constituents such as cannabinoids are typically lipophilic and thus formulations and routes of administration typically used for the delivery of lipophilic medicaments are suitable.

Suitable forms for oral administration include tablets, lozenges, pills, capsules, aerosols, elixirs, powders, granules, solutions, suspensions, emulsions, syrups, tinctures and herbal blends. For example, several cannabinoids and whole cannabis plant extracts have been developed as aerosol mouth sprays for oral administration, including Sativex^®. For topical administration the composition may be in the form of, for example, an ointment, cream, liniment, paste or lotion for administration via the skin or eye. One suitable form of topical delivery of a composition according to the present invention is via a skin patch. For example, US 6,113,940 (issued 5 September 2000 to Brooke et a/., the disclosure of which is incorporated herein by reference) describes suitable patches for the transdermal delivery of cannabis and cannabis constituents. The composition may be in a suitable form for intranasal administration, such as nasal inhalation. For example the composition may be delivered via an oil vaporizer, pressurised pump or as a pump-action spray.

Solid forms for oral administration may contain binders acceptable in human pharmaceutical practice, sweeteners, disintegrating agents, diluents, flavourings, coating agents, preservatives, lubricants and/or time delay agents. Suitable binders include gum acacia, gelatine, corn starch, gum tragacanth, sodium alginate, carboxymethylcellulose or polyethylene glycol. Suitable sweeteners include sucrose, lactose, glucose, aspartame or saccharine. Suitable disintegrating agents include corn starch, methylcellulose, polyvinylpyrrolidone, guar gum, xanthan gum, bentonite, alginic acid or agar. Suitable diluents include lactose, sorbitol, mannitol, dextrose, kaolin, cellulose, calcium carbonate, calcium silicate or dicalcium phosphate. Suitable flavouring agents include peppermint oil, oil of wintergreen, cherry, orange or raspberry flavouring. Suitable coating agents include polymers or copolymers of acrylic acid and/or methacrylic acid and/or their esters, waxes, fatty alcohols, zein, shellac or gluten. Suitable preservatives include sodium benzoate, vitamin E, alpha-tocopherol, ascorbic acid, methyl paraben, propyl paraben or sodium bisulphite. Suitable lubricants include magnesium stearate, stearic acid, sodium oleate, sodium chloride or talc. Suitable time delay agents include glyceryl monostearate or glyceryl distearate.

Liquid forms for oral administration may contain, in addition to the above agents, a liquid carrier. Suitable liquid carriers include water, oils such as olive oil, peanut oil, sesame oil, sunflower oil, safflower oil, arachis oil, coconut oil, liquid paraffin, ethylene glycol, propylene glycol, polyethylene glycol, ethanol, propanol, isopropanol, glycerol, fatty alcohols, triglycerides or mixtures thereof.

Suspensions for oral administration may further comprise dispersing agents and/or suspending agents. Suitable suspending agents include sodium carboxymethylcellulose, methylcellulose, hydroxypropylmethyl-cellulose, poly-vinyl-pyrrolidone, sodium alginate or acetyl alcohol. Suitable dispersing agents include lecithin, polyoxyethylene esters of fatty acids such as stearic acid, polyoxyethylene sorbitol mono- or di-oleate, -stearate or -laurate, polyoxyethylene sorbitan mono- or di- oleate, -stearate or -laurate and the like.

Emulsions for oral administration may further comprise one or more emulsifying agents. Suitable emulsifying agents include dispersing agents as exemplified above or natural gums such as guar gum, gum acacia or gum tragacanth.

The topical formulations of the present invention, comprise an active ingredient together with one or more acceptable carriers, and optionally any other therapeutic ingredients. Lotions or liniments for application to the skin may also include an agent to hasten drying and to cool the skin, such as an alcohol or acetone, and/or a moisturiser such as glycerol, or oil such as castor oil or arachis oil. Creams, ointments or pastes according to the present invention are semi-solid formulations of the active ingredient for external application. They may be made by mixing the active ingredient in finely-divided or powdered form, alone or in solution or suspension in an aqueous or non-aqueous fluid, with a greasy or non-greasy basis. The basis may comprise hydrocarbons such as hard, soft or liquid paraffin, glycerol, beeswax, a metallic soap; a mucilage; an oil of natural origin such as almond, corn, arachis, castor or olive oil; wool fat or its derivatives, or a fatty acid such as stearic or oleic acid together with an alcohol such as propylene glycol or macrogols.

For administration as an injectable solution or suspension, non-toxic parenteral^ acceptable diluents or carriers can include, Ringer's solution, isotonic saline, phosphate buffered saline, ethanol and 1,2 propylene glycol. Methods for preparing parenterally administrable compositions are apparent to those skilled in the art, and are described in more detail in, for example, Remington's Pharmaceutical Science, 15th ed., Mack Publishing Company, Easton, Pa., hereby incorporated by reference herein.

The compositions may also be administered in the form of liposomes. Liposomes are generally derived from phospholipids or other lipid substances, and are formed by mono- or multi-lamellar hydraled liquid crystals that are dispersed in an aqueous medium. Any non-ioxic, physiologically acceptable and metabolisable lipid capable of forming liposomes can be used. The compositions in liposome form may contain stabilisers, preservatives, excipients and the like. The preferred lipids are the phospholipids and the phosphatidyl cholines (lecithins), both natural and synthetic. Methods to form liposomes are known in the art, and in relation to this specific reference is made to: Prescott, Ed.,

Methods in Cell Biology, Volume XIV, Academic Press, New York, N.Y. (1976), p. 33 et seq., the contents of which is incorporated herein by reference.

Also included within the scope of the present invention is administration of cannabis constituents as prodrugs. Typically, prodrugs will be functional derivatives of the cannabis constituents which are readily converted in vivo to the required constituents. Typical procedures for the selection and preparation of prodrugs are known to those of skill in the art and are described, for instance, in H.

Bundgaard (Ed), Design of Prodrugs, Elsevier, 1985, the disclosure of which is incorporated herein by reference.

The present invention will now be described with reference to specific examples, which should not be construed as in any way limiting the scope of the invention.

Examples

Example 1: Research protocol examining the relationship between cannabis use and cognitive functions in Schizophrenia The results described below are based on Research Protocol 0201-006M (SP) approved by the

Northern Sydney Health Human Research Ethics Committee: "The Effects of Cannabis on Neuropsychological Functioning in Schizophrenia". 1.1 Participants: Inclusion / exclusion criteria

59 males between the ages of 17 and 44 years with a DSM-IV diagnosis of Schizophrenia or Schizoaffective Disorder from mental health clinics in the Northern Sydney and Mid Western Area Health Services, NSW Australia were recruited and assessed between July 2002 and February 2003. To be included in the research, the participants needed to have or be: i. A diagnosis of a Schizophrenia Spectrum Disorder according to DSM-IV criteria ii. No other identified Axis I Disorder (current or past) according to DSM-IV criteria, with the exception of a substance use disorder iii. Aged between 17 and 45 years, iv, Proficient in English v. Based in the community, psychiatrically stable at the time of recruitment, and able to consent to participation vi. Of male gender justified on grounds that males predominantly constitute the psychosis and comorbid substance use populations (Kavanagh et a/., 2004, Schizophrenia Research 66:115- 124), and to avoid the confounding effects of gender differences known to exist with respect to the neurobiological and neuropsychological profiles of Schizophrenia sufferers (Antonova et ai, 2004, Schizophrenia Research 70:117-145) vii. No alcohol or recreational illicit drug use within 24 hours of cognitive assessment, as confirmed by the absence of such substances in urine samples viii. No nicotine intake within one hour of commencing cognitive assessment, being a conservative precautionary measure on grounds that the effects of nicotine on cognition are acute, generally lasting only 10 minutes at most after ingestion (Sakurai and Kanawaza, 2002, Hum

Psychopharmaco! Clin Exp 17:369-373). Furthermore, studies of nicotine abstinence of up to 24 hours in regular users have described the "tobacco withdrawal syndrome" characterised by craving, irritability, restlessness, and impairment on tasks of memory, attention, and concentration (Hirshman ef a/., 2004, Experimental and Clinical Psychopharmacology 12:76-83). Hence, regular nicotine users were not required to refrain from smoking in the 24 hours prior to cognitive assessment to avoid the confounding impact of the tobacco withdrawal syndrome ix. No caffeine consumption within one hour prior to cognitive assessment and no caffeine abstinence within 24 hours prior to cognitive assessment due to the effects of acute caffeine intake as well as caffeine deprivation on cognition and mood (for a review see Schapkin, 2002,

Human Physiology, 28:128-133) x. No history of sustained brain injury or other neurological illness. Given the high rates of neurological events in Schizophrenia and the vast body of research devoted to the relationship between psychosis and traumatic brain injury/neurological events (e.g., Malaspina et a\,, 2001, American Journal of Psychiatry 158:440-446), the following sub-criteria were explicitly defined: a. No documented evidence of LOC (loss of consciousness) greater than a few minutes b. No documented evidence of hospitalisation greater than one day for treatment or rehabilitation associated with head trauma or neurological illness (i.e., any hospitalisation required for management of injuries other than superficial wounds) c. No documented evidence of Post-Traumatic Amnesia (PTA) d. No documented evidence of brain abnormalities as ascertained by Computerised Tomography (CT), Magnetic Resonance Imaging (MRI), Electroencephalogram (EEG), or other neurological investigations e. No sustained period of other medical treatment required for neurological illness (e.g., anticonvulsant medications) xi. No evidence of a Developmental or Intellectual Disability/Disorder. 1.2 Dependent measures Psychiatric measures The Research Version of the Psychotic Disorders module of the Structured Clinical Interview for

DSM-IV (SCID-I: First ef a/., 2001 , Users Guide for the Structured Clinical Interview for DSM-IV-TR Axis I Disorders- February 2001 Revision; Ventura ef a/., 1998, Psychiatric Research 79:163-173) was used to confirm diagnosis of Schizophrenia or Schizoaffective Disorder and obtain a detailed psychiatric history, including medications. The Schedules for Assessment of Negative Symptoms and Positive Symptoms (SANS and SAPS respectively: Andreasen, 1983, The Scale for the Assessment of Negative Symptoms (SANS), University of Iowa; Andreasen, 1984, The Scale for the Assessment of Positive Symptoms (SAPS), University of Iowa) were administered to rate current severity of positive and negative symptoms. The Depression Anxiety Stress Scales (DASS: Lovibond & Lovibond, 1995, Behaviour

5 Research & Therapy 33:335-343) and Calgary Depression Scale (CDS: Addington et al, 1993, British Journal of Psychiatry 163 (Suppl.22):39-44) were administered to assess depression, anxiety and stress symptoms.

Substance use measures

The Research Version of the Substance Use Disorders module of the Structured Clinical Interview o for DSM-IV (SCID-I: First et al., 2001; Ventura et al. 1998) was used to determine current and lifetime history of substance abuse/dependence. Additional semi-structured questionnaires adapted from Barry et al. (1995, Schizophrenia Bulletin 21:313-321) were used to attain a more detailed history of drug and alcohol use with respect to recency, quantity, frequency, and duration of use over lifetime. Specifically, any level of cannabis use (including abuse/dependence according to DSM-IV criteria as well as non- 5 dependent use) was staged with respect to the frequency and quantity of use within the past week, past month, past 12 months, and lifetime. For example, a participant may be classified with lifetime cannabis abuse/dependence but may not have used any cannabis in the past week, past month, or past 12 months. Another participant may have used cannabis at a non-dependent level in the past week, but may not have met criteria for abuse/dependence at any period in his life. o Cognitive measures

Cognitive assessment comprised estimate of premorbid intelligence by the Shipley Institute of Living Scale: Vocabulary Component (Shipley, 1946, Institute of Living Scale, Los Angeles, Western Psychological Services) and measurement of functioning within four domains of cognition. These were 1) attention and processing speed, 2) executive functions, 3) memory, and, 4) perceptual organisation. 5 The specific tests used to assess performance within each cognitive domain are detailed in Table 1. 1.3 Procedure

Entire assessment took place over two visits, approximately 24 hours apart. Assessment was conducted either in the privacy of each participant's home or at the local hospital site. On the first visit, demographic details (i.e., date of birth, years of education, source of income, living situation, marital 0 status etc.) were obtained as well as assessment of medical, neurological, developmental, and psychosocial history; psychiatric symptoms/diagnosis; mood and anxiety; recency, frequency, quantity, and duration of substance use; and current/past substance abuse/dependence. The first visit included administration of the Structured Clinical Interview for DSM-IV (SCID-I: Psychotic Disorders and Substance Use Disorders modules), Schedule for Assessment of Negative Symptoms (SANS), Schedule 5 for Assessment of Positive Symptoms (SAPS), Calgary Depression Scale (CDS), Depression Anxiety Stress Scales (DASS), and the substance use questionnaire adapted from Barry et al. (1995). Duration of the first visit was between one and a half to two and a half hours. At the end of the first visit, participants were reminded not to consume alcohol or use illicit drugs over the following 24 hour period, or to smoke any cigarettes/consume caffeine within one hour prior to the scheduled session for cognitive assessment the following day. A urine sample was also taken at the end of the first visit (see below for more detail on the procedure for urine analysis),

Cognitive assessment was performed on the second visit, approximately 24 hours later. On arrival, the researcher initially "filled in" time setting up the laptop computer for assessment, obtained a 5 second urine sample, and engaged in general conversation with the participants to maximise the amount of time since most recent self-reported caffeine or nicotine intake, verifying an additional 30 minutes abstinence from nicotine and caffeine. Assessment of cognitive functioning was subsequently performed which endured approximately two hours.

Drug screening io Participants were requested to refrain from all recreational drug use in the 24 hours prior to cognitive assessment. The two urine samples obtained on the first and second visits were used to screen for cannabis use during the intervening 24 hours. The rationale for taking two urine samples 24 hours prior to and just before assessing cognitive functions was as follows:

The primary psychoactive constituent of cannabis is Δ-9-tetrahydrocannabinol (Δ9-THC). i₅ Because Δ9-THC and cannabinoids are extremely lipid soluble, they accumulate in fatty tissue and are slowly released back into body compartments, including the brain. The tissue elimination half life of Δ9-

THC is between 4-12 days, and complete elimination of a single dose may take up to 30 days.

Consequently, recency of cannabis use cannot be determined from a single urine sample. Amount of cannabis in the urine is indicated by the "creatinine normalised urinary cannabinoid metabolite level" (or 0 carboxy-THC creatinine ratio). If a cannabis user refrains from use for a period of at least 24 hours, the

Δ9-THC creatinine ratio in the second urine sample will be proportionally lower (i.e., approximately 50% less) than the first (Huestis & Cone, 1998, Journal of Analytical Toxicology 22:445-454). Thus, comparing the carboxy-THC creatinine ratio in the two urine samples from a given individual made it possible to determine if the individual had used cannabis within the previous 24 hours. ₅ Moreover, the second urine sample was used to screen for the presence of other recreational drugs including alcohol, nicotine, caffeine, amphetamines, sedatives, cocaine, opioids and hallucinogens at the time of cognitive assessment.

The second urine sample was also taken to ascertain quantity of THC in the urine at the time of cognitive assessment to validate that the distinction in cognitive performance between cannabis using 0 subgroups was attributable to respective levels of THC in those who were deemed high, medium, and low/nil frequency users, as well as those who were deemed recent users and non-recent or nil users. The results from urine analysis validated that with the exception of caffeine and nicotine (which were permitted within 24 hours of cognitive assessment but not within one hour of cognitive assessment as discussed above), as well as cannabis (being the primary substance of interest), there was no 5 evidence of alcohol or other recreational substance use at the time of cognitive assessment.

1.4 Data reduction

The full data set comprised 67 cognitive measures and 13 psychiatric measures. Table 1 lists all the cognitive measures within each of the four cognitive domains, and Table 2 lists the full range of psychiatric measures. Prior to analyses of neuropsychological and psychiatric variables, the raw data set was screened for anomalies, using the guidelines and procedures proposed by Tabachnick and Fidell (2001 , Using

Multivariate Statistics, Fourth Edition, Allyn & Bacon, pp 56-110). Specifically, the following steps were carried out: i. Screening for univariate outliers who were deemed not solely representative of the Schizophrenia population ii. Exploring cases of missing data and managing the problem. In this instance, technical difficulties during administration of the CogState computerised battery occurred for 3 participants on a subset of tasks. Given that these cases of missing data occurred in a random fashion and for only a very small percentage of data points (i.e., less than 5%), their missing scores were substituted by the overall mean scores of the full Schizophrenia group, a procedure which is considered conservative and does not change the mean of the Schizophrenia distribution as a whole (Tabachnick and Fidell, 2001). iii. Identifying and dealing with variables that were non-normally distributed: a. Checking skewness and kurtosis of each variable b. Transforming variables to reduce significance of skewness and kurtosis and to reduce the influence of extreme scores exceeding 3.0 standard deviations either side of the group mean c. Deleting variables which could not be adequately transformed iv. Addressing the issue of nonlinearity and heteroscedasticity v. Identifying and dealing with multivariate outliers vi. Evaluating variables for multicollinearity and singularity and deleting variables which contributed significantly to these problems.

Following the full data screening and cleaning process described above, Tables 3 and 4 list the full set of cognitive and psychiatric measures respectively that were subjected to Principal Components

Analysis (PCA). The number of measures listed in Table 3 is less than the full set listed in Table 1. This is because the skewness/kurtosis of some measures was so severe that scores were unamenable to transformation and that measure was therefore deleted from the set. Also, measures which contributed significantly to multicollinearity or singularity were excluded from analysis. The direction of scores in Tables 3 and 4 are also specified for each measure. The direction of scores for the measures were dependent on the type of transformation (if any) applied to the data, and also on whether measures were positively or negatively skewed.

The neuropsychological measures within each cognitive domain and the psychiatric variables listed in Tables 3 and 4 were subjected to PCA for the Schizophrenia group (N=59) for the purpose of reducing this large data set down to a smaller number of components. Measures within each cognitive domain were subjected to individual PCAs rather than the entire set of all cognitive measures being subjected to one single PCA for two reasons. First, the purpose of performing PCA in the present research was simply to reduce the number of variables, not to confirm underlying factor structures of already pre-established standardised measures of cognition. Second, a recommended minimum of five participants per variable is usually required for generating a stable and reliable PCA solution (Gorsuch, 1983, cited in Osborne and Costello, 2004, Praciical Assessment, Research & Evaluation 9: article retrieved from http://PARonline.net/getvn.asp?v=9&n=11).

Table 5 lists the final set of 21 cognitive components that were reduced by PCA from the full set of cognitive measures listed in Table 3. Table 6 lists the final set of 3 psychiatric components that were reduced by PCA from the full set of psychiatric measures listed in Table 4. The "labels" assigned to these components reflected the types of measures listed in Tables 3 and 4 respectively which loaded on each component (see Tabachnick and Fidell, 2001 for a comprehensive review of the PCA process). The overall direction of each of the 21 cognitive components and 3 psychiatric components was influenced by the direction in which each individual measure listed in Tables 3 and 4 loaded on the components. 1.5 Description of the Schizophrenia group

The mean age of the Schizophrenia group was 26.39 years (SD = 5.35), mean number of years of education was 12.32 (SD = 1.77), mean duration of mental illness (i.e., number of years since first contact with a mental health service and commencement on antipsychotic medication) was 4.93 (SD = 3.83), and mean estimated premorbid intelligence (as measured by the Shipley Institute of Living Scale: Vocabulary Component) was at the 45.61^st percentile (SD = 27.18).

Antipsychotic medications were prescribed to 58 participants (98.3%). The remaining 1 participant (1 ,7%) was considered to be functioning adequately without the need for this medication. Of the 58 participants prescribed an antipsychotic agent, 4 (6.8%) were non-compliant at the time of assessment, 1 (1.7%) was taking a typical antipsychotic drug (haloperidol), 52 were taking atypical antipsychotic drugs (clozapine, olanzapine, risperidone, quetiapine) and 8 (13.3%) were on depot neuroleptic injections (flupenthixol decanoate, zuclopenthixol decanoate, fluphenazine decanoate). Anticholinergics (atropine sulfate, benztropine mesylate) were prescribed to 3 participants (5%), antidepressants (citalopram, sertraline, paroxetine, venlafaxine, mirtazepine, fluoxetine) were prescribed to 22 participants (37.3%), mood stabilisers (sodium valproate, carbamazepine, lamotrigine) were prescribed to 18 participants (30.5%), and sedatives (temazepam, diazepam, clonazepam) were prescribed to 7 participants (13.6%), all of whom were complying at the time of assessment. The full range of psychiatric medications described here and their potential cumulative effects on cognition in those who were prescribed more than one medication were examined as potential covariates on cognitive performance, as discussed later in Section 1.6.

With respect to other "non-psychiatric" medications, 1 participant (1.7%) was taking pain relief medication (prn) following a recent surgical procedure and 3 participants (5.1%) were currently taking cold and flu tablets (prn). The presence of opiates in the urine samples for these participants reflected the codeine contained in the medications which was metabolised as morphine. The use of these non- psychiatric medications was explored as a potential covariate on cognitive performance, as discussed in Section 1.6 below.

With respect to current cannabis use, 18 participants (30.5%) reported use within the past week which was confirmed by the presence of cannabis in their urine samples. Of these 18 users, comparison between the firsl and second urine analyses indicated thai 12 (20.3%) had refrained from cannabis use in the 24 hour period prior to cognitive assessment whilst 6 (10.2%) did not refrain. Acute cannabis use was therefore examined as a confounding variable as discussed in Section 1.6, but did not emerge as a significant covariate on any of the 21 cognitive components. Within the month prior to assessment, 1 participant (1.7%) met DSM-IV criteria for alcohol abuse/dependence and 1 participant (1.7%) met criteria for sedatives abuse/dependence, however, neither of these participants used/abused within 24 hours prior to cognitive assessment. Nevertheless, for the purpose of rigorous analysis, these cases of substance abuse/dependence in the past month were examined as a potential covariate on cognitive performance, as discussed in Section 1.6. Within the past 12 months, 3 participants (5.1%) met criteria for other substance abuse/dependence, 2 pertaining to alcohol and 1 to sedatives as described in the previous paragraph. The remaining 56 participants (94.9%) did not meet criteria for substance abuse/dependence (not including cannabis) in the 12 month period preceding recruitment. Although other such recreational substance abuse/dependence did not pertain to 24 hours prior to cognitive assessment, again, substance abuse/dependence in the past 12 months was examined a potential covariate on cognitive performance, as discussed in Section 1.6.

With respect to lifetime history of substance use, 27 participants (45.8%) met criteria for substance abuse/dependence other than cannabis. Of these, 6 (10.2%) pertained to alcohol, 3 (5.1%) to amphetamines, 3 (5.1%) to hallucinogens, and the remaining 15 (25.4%) met criteria for abuse/dependence for a combination of two or more substances including alcohol, opioids, amphetamines, cocaine, and sedatives. Lifetime substance abuse/dependence described here was examined as a potential covariate on cognitive performance, as was the potential cumulative effects on cognition for those who met criteria for more than one other substance of abuse/dependence, as discussed in Section 1.6. In the month prior to assessment, 40 participants (67.8%) reported smoking cigarettes on a daily basis and 3 participants (5.1%) reported smoking between 1 and 3 days per week. Nicotine was present in the urine samples of these 43 participants (72.9%) at the time of cognitive assessment, Although no nicotine use within one hour of cognitive assessment was ensured, current nicotine use described here was nevertheless examined as a potential covariate on cognitive performance, as discussed in Section 1.6.

In the month prior to assessment, 41 participants (69.5%) reported caffeine consumption on a daily basis (e.g., tea, coffee, coca cola) and an additional 16 participants (27.1%) reported caffeine consumption between 1 and 5 days per week. Caffeine was present in the urine samples of 50 participants (84.7%) at the time of cognitive assessment. Again, although no caffeine use within one hour of cognitive assessment was ensured, current caffeine use described here was nevertheless examined as a potential covariate on cognitive performance, as discussed in Section 1.6.

In the month prior to assessment, 27 participants (45.8%) reported alcohol consumption in the past week, 15 (25.4%) reported alcohol consumption in the past month, and the remaining 17 (28.8%) reported no alcohol consumption in the past month. Although there was no alcohol present in the urine samples of any participant at the time of cognitive assessment, current alcohol use was nevertheless examined as a potential covariate on cognitive performance, as discussed in Section 1.6.

With respect to other illicit substance use in the month prior to assessment, 2 participants (3.4%) reported non-dependent use, 1 pertaining to ecstasy, and 1 to amphetamines, There were no traces of these substances in the urine samples at the time of cognitive assessment, however, recent illicit substance use was nevertheless examined as a potential covariate on cognitive performance, as discussed in Section 1.6. 1.6 Covariates within the Schizophrenia group

As outlined above, a wide range of confounding variables were explored within the entire Schizophrenia group to determine their influence on the 21 cognitive components, and were subsequently controlled where they demonstrated a significant effect on neuropsychological performance. They included the following: i. Early-age onset of mental illness (as defined by when first contact was made with a mental health service and commenced on psychiatric medications) ii. Duration of mental illness (number of years since first contact with a mental health service and commencement on psychiatric medications) iii. Number and types of psychiatric medications currently taken (e.g., conventional and atypical antipsychotics, antidepressants, mood stabilisers, sedatives, and anticholinergics) iv. Non-psychiatric medications currently taken v, Caffeine, nicotine, and alcohol use in the past week and month vi. Non-dependent substance use in the past month (except cannabis) vii. Substance abuse/dependence in the past month (except cannabis) viii. Substance abuse/dependence in the past 12 months (except cannabis) ix. Lifetime substance abuse/dependence (except cannabis) x. Early-age onset of cannabis, alcohol, nicotine, and other illicit substance use xi, Duration of regular lifetime cannabis, alcohol, nicotine, and other illicit substance use xii. Acute cannabis use (use in the 24 hours preceding assessment). In summary of exploring these covariates, the following were identified as significant: First, independent samples t-tests showed that 15 participants who had consumed alcohol in the past month (excluding users in the past week) performed significantly worse than the remaining 17 participants who had not consumed alcohol in the past month on the Complex Perceptual Organisation cognitive component (feo = -4.89, pθ.001). Subsequently, alcohol use in the past month was entered as a covariate in all analyses pertaining to this cognitive component.

Second, independent samples t-tests showed that 2 participants who met DSM-IV criteria for other substance abuse/dependence in the past month performed significantly better than the rest of the group on the Visual Scanning Speed cognitive component (fez = 4.98,p<0.001). In all analyses involving this cognitive component, the data from these 2 participants were excluded.

Third, independent samples t-tests showed that 2 participants who used other illicit substances at a non-dependent level in the past month performed significantly better than the rest of the group on the Simple Perceptual Organisation cognitive component (ts? = -7.44, pθ.001), and significantly worse than the rest of the group on the Cognitive Flexibility component ({57 = -8.40, p<0.001). In all analyses involving these two cognitive components, the data from these 2 participants were excluded.

No other covariates from the list above were identified as exerting a significant impact on any of 5 the 21 cognitive components.

In addition to exploring a range of covariates within the entire Schizophrenia group, a range of other covariates were explored specifically between cannabis subgroups as will be described in later sections. These covariates were: age, years of education, premorbid intellectual functioning, and severity of positive symptoms, negative symptoms, and mood/anxiety symptoms. 0 1.7 Frequency of cannabis us©

Frequency of cannabis use in the Schizophrenia group was defined according to regular patterns of self-reported use over the year preceding assessment. 11 participants reported regular use of cannabis between weekly and daily throughout the past year, and hence, were deemed high frequency users. Another 7 participants reported use of cannabis between two and four times per month regularly 5 throughout the past year, and hence, were deemed medium frequency users. Finally, 34 participants reported either nil use or virtually nil cannabis use throughout the past year (which was generally only once every few months at most) and hence, were deemed low frequency users. These frequency of cannabis use indices were validated by the mean creatinine normalised urinary cannabinoid metabolite levels (i.e., carboxy-THC creatinine ratio) in the urine samples at the time of cognitive assessment which o were 519 ng/mg, 195 ng/mg, and 0 ng/mg for the high, medium, and low frequency subgroups respectively. All participants in the low frequency subgroup had a carboxy-THC creatinine ratio of 0 ng/mg at the time of cognitive assessment.

The remaining 7 participants in the Schizophrenia group were intermittent cannabis users over the preceding year whereby frequency of cannabis use was not consistent or regular. For the purposes of 5 focusing on regular frequency of cannabis use, these latter 7 were excluded from the analyses reported herein.

Covariates

Demographic, premorbid intelligence, and psychiatric variables

Table 7 contains information pertaining to age, years of education, premorbid intelligence, duration Q of mental illness, and psychiatric component scores for participants within each frequency subgroup. As can be seen in Table 7, One-Way Analysis of Variance revealed no significant differences between the three frequency subgroups on any of the demographic, premorbid intelligence, or psychiatric variables

(p>0.05).

Lifetime cannabis abuse I dependence and recency of cannabis use 5 In order to examine "pure" associations between any given cannabis use index and cognition, other patterns of cannabis use should be controlled for their potential confounding effects. In examining the relationship between frequency of cannabis use and cognition in Schizophrenia, both lifetime cannabis abuse/dependence and recency of cannabis use were examined as potential covariates and controlled accordingly. Both lifetime cannabis abuse/dependence and recency of cannabis use stratified by frequency of cannabis use are presented in Table 8.

As can be seen in Table 8, all high and medium frequency cannabis users in the preceding year also met criteria for lifetime cannabis abuse/dependence, whilst a substantially smaller proportion of low frequency cannabis users had met criteria for lifetime cannabis abuse/dependence. Chi-square tests accordingly supported a significant relationship between lifetime cannabis abuse/dependence and frequency of cannabis use in the past year (χ²=11.16, df=2, p=0.002). In further exploring bivariate differences, lifetime cannabis abuse/dependence was significantly related to high vs low frequency use (χ²=7.28, df=1, p=0.008), and to medium vs low frequency use (χ²=4.87, df=1, p=0.035), but was constant for both high and medium frequency use, therefore, not significant (p>0.05).

Similarly, strong relationships emerged between frequency of cannabis use in the past year and recency of both non-dependent cannabis use and abuse/dependence. Specifically, the largest proportion of participants who did not use cannabis at either a non-dependent or dependent level in the past month comprised low frequency cannabis users, whilst the largest proportion of participants who used cannabis at a non-dependent level in the past month comprised medium frequency cannabis users. Moreover, the largest proportion of participants who met criteria for cannabis abuse/dependence in the past month comprised high frequency cannabis users. Accordingly, non-dependent cannabis use in the past month was significantly related to high vs medium frequency use (χ²=10.57, df=1, p=0.002), and to medium vs low frequency use (χ²=20.03, df=1, p<0.001), but not to high vs low frequency use (p>0.05). Moreover, cannabis abuse/dependence in the past month was significantly related to high vs medium frequency use (χ²=10.57, df=1, p=0.002), and to high vs low frequency use (χ²=39.74, df=1, p<0.001), but not to medium vs low frequency use (p>0.05). Other covariates As described above in Section 1.6, the 2 participants who met criteria for other substance abuse/dependence in the past month were excluded from analyses pertaining to the Complex Perceptual Organisation component, and the 2 participants wh^'o used other illicit substances at a non- dependent level in the past month were excluded from analyses pertaining to the Visual Scanning and Cognitive Flexibility components. Moreover, alcohol use in the past month was controlled in analyses pertaining to the Complex Perceptual Organisation component. Results of logistic regressions

The results from univariate logistic regressions for the three frequency cannabis use subgroups are presented in Table 9 which details the mean scores and standard deviations for all 21 cognitive components within each frequency subgroup, chi-square statistics for each binary logistic regression, and the full range of covariates that were controlled in the analyses. The components which are shaded in grey denote those on which a lower score reflected better performance, and mean scores that are highlighted in bold for each component represent which of the three subgroups performed the best as distinguished by logistic regressions.

As can be seen in Table 9, results yielded from logistic regression analyses for the high vs low frequency subgroups which approached statistical significance (i.e., p≤0.05) included Speed of Information Processing (χ²=4.77, df=1, p=0.029, Nagelkerke R²=0.96, classification rate=95.6%), Visual Scanning (χ²=3.83, df=1, p=0.05, Nagelkerke R²=0.95, classification rate=95.3%), and Inhibition Accuracy (χ²=4.80, df=1, p=0.028, Nagelkerke R²=0.97, classification rate=95.6%), with the high frequency users performing better than the low frequency users on all three components. The results yielded from logistic regression analyses for the high vs medium frequency subgroups which approached statistical significance included Complex Perceptual Organisation (χ²=5.43, df=1, p=0.020, Nagelkerke R²=0.92, classification rate=88.9%) and Simple Perceptual Organisation (χ²=5.74, df=1, p=0.017, Nagelkerke R²=1.00, classification rate=100.0%), with the high frequency users performing better than the medium frequency users on both components, Moreover, results pertaining to analyses of the high vs medium frequency groups which reached statistical significance (i.e., p≤0.002 according to Bonferroni adjustment of α=0.05/21 cognitive components) included Divided Attention (χ²=12.44, df=1, p<0.001, Nagelkerke R²=1.00, classification rate=100.0%) and Planning Efficiency (χ²=12.44, df=1, p<0.001, Nagelkerke R²=1.00, classification rate=100.0%), with the high frequency users performing better than the medium frequency users on both components Results yielded from logistic regression analyses for the medium vs low frequency subgroups which approached statistical significance included Verbal Conceptual Switching (χ²=4.89, df=1, p=0.027, Nagelkerke R²=0.78, classification rate=97.6%), Visual Conceptual Switching (χ²=6.07, df=1, p=0.014, Nagelkerke R²=0.80, classification rate=97.6%), and Cognitive Flexibility (χ²=5.74, df=1, p=0.017, Nagelkerke R²=1.00, classification rate=100.0%), with the medium frequency users performing better than the low frequency users on the former component, and worse than the low frequency users on the latter two components.

A summary of the main findings from these logistic regressions is presented in Figure 1. The solid line represents the total number of components on which each subgroup performed better than the other two subgroups as distinguished by logistic regressions, and the dotted line represents the number of components on which each subgroup performed worse than the other two subgroups as distinguished by logistic regressions.

The solid line in Figure 1 shows that high, medium, and low frequency use was associated with better performance compared to the other two subgroups on seven, one, and two components respectively where binary logistic regressions significantly distinguished performance between the subgroups (i.e., p≤0.002) or approached significance (i.e., p≤0.05), The dotted line shows that high, medium, and low frequency use was associated with worse performance compared to the other two subgroups on zero, five, and four components respectively where binary logistic regressions significantly distinguished performance between the subgroups or approached significance.

In summary, high frequency cannabis use was associated with the best overall performance on at least one third of all cognitive components and was the only subgroup for which worse performance compared to the other two subgroups was not identified on any components which significantly distinguished between the subgroups. Both the medium and low frequency users demonstrated relatively comparable performance to each other, thereby demonstrating that regardless of whether cannabis is used at a medium or low frequency level, no substantial difference in cognitive performance between groups is identified. Evidently, high frequency cannabis use in Schizophrenia is a hallmark factor in influencing neuropsychological functioning. 1.8 Lifetime cannabis abuse / dependence

44 of the 59 Schizophrenia participants met DSM-IV criteria for lifetime cannabis abuse/dependence.

Covariaies

The procedures for examining covariates for lifetime cannabis abuse/dependence were the same as those described for frequency of cannabis use above in Section 1.7.

With respect to demographic, premorbid intelligence, and psychiatric variables, One-Way Analysis of Variance revealed a significant difference between groups with and without a lifetime diagnosis of cannabis abuse/dependence pertaining to age (Fi,57=9.36, p=0.031), with users being older than non- users, and duration of mental illness (Fi,57=6.32, p=0.003), with users having a longer duration of mental illness than non-users. Both age and duration of mental illness were therefore entered as covariates in univariate logistic regression analyses. There were no significant differences between the groups in relation to years of education, premorbid intelligence, or psychiatric variables (p>0.05),

With respect to other potential confounding cannabis use patterns for lifetime cannabis abuse/dependence, both recency of cannabis use (i.e., abuse/dependence in the past month and non- dependent use in the past month) and frequency of cannabis use were explored. In brief, the relationship between cannabis abuse/dependence in the past month and lifetime cannabis abuse/dependence was statistically significant (χ²=5.14, df=1 , p=0.026), as was the relationship between frequency of cannabis use in the past year and lifetime cannabis abuse/dependence (χ²=14.79, df=3, p=0.002). With respect to which aspects of frequency of cannabis use were most associated with lifetime cannabis abuse/dependence, significant relationships emerged between low frequency cannabis use and lifetime cannabis abuse/dependence (χ²=14.79, df=1, p<0.001), and between high frequency cannabis use and lifetime cannabis abuse/dependence (χ²=4.61, df=1, p=0.05), but not between either medium or intermittent frequency cannabis use and lifetime cannabis abuse/dependence (p>0.05).

There was no significant relationship between non-dependent cannabis use in the past month and lifetime cannabis abuse/dependence (p>0.05). In sum, the covariates entered into the logistic regression analyses for lifetime cannabis abuse/dependence were age, duration of mental illness, cannabis abuse/dependence in the past month, and high/low frequency cannabis use in the past year. Moreover, as explained in Section 1.6, the 2 participants who met criteria for other substance abuse/dependence in the past month were excluded from analyses pertaining to the Complex Perceptual Organisation component, and the 2 participants who used other illicit substances at a non- dependent level in the past month were excluded from analyses pertaining to the Visual Scanning and Cognitive Flexibility components. Alcohol use in the past month was also controlled in analyses pertaining to the Complex Perceptual Organisation component.

Results of logistic regressions

The results of logistic regressions showed that none of the 21 cognitive components significantly distinguished between those with and without a lifetime history of cannabis abuse/dependence (p>0.05). These results were not unexpected given that lifetime cannabis abuse/dependence is a very broad and gross definition of substance use, regardless how rigorously it is examined. A diagnosis of lifetime cannabis abuse/dependence encompasses a heterogenous population of individuals who can vary markedly with respect to frequency, recency, and duration of drug use. Conflating both past and current 5 users as well as those with a mixture of current cannabis use patterns is bound to obfuscate the connection between cannabis use and cognition in Schizophrenia, and when other such patterns of use are controlled (as they were in these analyses), users are not significantly distinguished from non-users. 1.9 Recency of cannabis use

11 Schizophrenia participants met criteria for cannabis abuse/dependence in the past week. Of o note, 10 of these 11 participants were described above in Section 1.7 who comprised high frequency cannabis users. In addition, 7 Schizophrenia participants reported non-dependent cannabis use in the past week, another 7 reported most recent non-dependent cannabis use prior to the past week but within the past month, and 9 participants reported most recent non-dependent cannabis use prior to the past month. s In sum, there were four recency of cannabis use subgroups, being cannabis abuse/dependence in the past week (n=11 users), non-dependent cannabis use in the past week (n=7 users), most recent non-dependent cannabis use in the past month (n=7 users), and most recent non-dependent cannabis use prior to the past month (n=9 users). Recency of cannabis use for the first two subgroups (i.e., cannabis abuse/dependence in the past week and non-dependent cannabis use in the past week) were 0 validated by the mean creatinine normalised urinary cannabinoid metabolite levels on the day of cognitive assessment (i.e., carboxy-THC creatinine ratio) which were 524 ng/mg and 188 ng/mg respectively. For those who reported most recent non-dependent cannabis use within the past month (but prior to the past week) as well as those who reported most recent non-dependent cannabis use prior to the past month, the carboxy-THC creatinine ratio in the urine samples were 0 ng/mg for all participants 5 at the time of cognitive assessment, indicating full excretion of any pre-existing levels of THC at the time of cognitive assessment. Covariates

The procedures for examining covariates for each of the four recency subgroups were the same as those described for frequency of cannabis use above in Section 1.7. o With respect to demographic, premorbid intelligence, and psychiatric variables, One-Way Analysis of Variance revealed a significant difference between non-dependent cannabis users in the past week and non-users pertaining to premorbid intellectual functioning (Fi,46=4.39, p=0.042), with users having a lower score than non-users; premorbid IQ was therefore entered as a covariate in analyses for this recency index. For most recent non-dependent cannabis use in the past month (excluding use in the 5 past week), One-Way Analysis of Variance revealed a significant difference between users and non- users pertaining to duration of mental illness (Fi,3β=4.98, p=0.032), with users having a longer mean duration than non-users; duration of mental illness was therefore entered as a covariate in analyses for this recency index. There were no other significant differences between users and non-users within each of the four recency subgroups on demographic, premorbid intelligence, or psychiatric variables. With respect to other potential confounding cannabis use patterns for recency of cannabis use, both frequency of cannabis use and lifetime cannabis abuse/dependence use were explored. In brief, lifetime cannabis abuse/dependence was significantly related to cannabis abuse/dependence in the past week (χ²=5.66, df=1, p=0.022), but not with the other three recency of cannabis use indices (p>0.05). Moreover, cannabis abuse/dependence in the past week was significantly related to low frequency of cannabis use in the past year (χ²=24.23, df=1, p<0.001) and high frequency cannabis use in the past year (χ²=46.15, df=1, pθ.001), both of which were controlled in the analyses for cannabis abuse/dependence in the past week. Non-dependent cannabis use in the past week was significantly related to low frequency cannabis use in the past year (χ²=12.68, df=1, p=0.001) and medium frequency cannabis use in the past year (χ²=14.93, df=1, p=0.002), both of which were controlled in the analyses for non-dependent cannabis in the past week. Most recent non-dependent cannabis use in the past month was significantly related to low frequency cannabis use in the past year (χ²=17.09, df=1, p=0.001) and medium frequency cannabis use in the past year (χ²=9.93, df=1, p=0.027), both of which were controlled in the analyses for non-dependent cannabis use in the past month. Lastly, most recent non- dependent cannabis use prior to the past month was not significantly related frequency of cannabis use in the past year (p>0.05), therefore, no covariates were entered for non-dependent cannabis use prior to the past month.

In addition, as explained in Section 1.6, the 2 participants who met criteria for other substance abuse/dependence in the past month were excluded from analyses pertaining to the Complex Perceptual Organisation component, and the 2 participants who used other illicit substances at a non- dependent level in the past month were excluded from analyses pertaining to the Visual Scanning and Cognitive Flexibility components. Alcohol use in the past month was also controlled in analyses pertaining to the Complex Perceptual Organisation component.

Results of logistic regressions The results of logistic regression analyses failed to substantially distinguish between users and non-users within each of the four recency of cannabis use subgroups. In fact, those who met criteria for cannabis abuse/dependence in the past week performed better than non-users on only one cognitive component (i.e., Complex Perceptual Organisation: χ²=6.28, df=1, p=0.012, Nagelkerke R²=1.00, classification rate=100.0%). This was somewhat unexpected in context of the fact that the majority of participants who were deemed high frequency cannabis users in Section 1.7 were the same participants who met criteria for cannabis abuse/dependence in the past week.

Given that frequency of cannabis use was the only covariate entered in logistic regression analyses for cannabis abuse/dependence in the past week, these results demonstrated that frequency of cannabis use is evidently a stronger predictor of cognitive performance in Schizophrenia than recency of use, because when frequency of use is controlled, cognitive performance fails to substantially differentiate users from non-users. 1.10 Summary

Results for frequency of cannabis use demonstrated that high frequency use over the year preceding assessment was associated with better cognitive performance than both medium and low/nil frequency use on all cognitive components which distinguished performance between the 3 subgroups by logistic regressions. These results were yielded in context of controlling a range of covariates including lifetime cannabis abuse/dependence and recency of cannabis use.

No significant relationships emerged between lifetime cannabis abuse/dependence and cognition in Schizophrenia on any of the 21 cognitive components, which was not unexpected, in context of the fact that lifetime cannabis abuse/dependence is a very broad and gross index of cannabis use which conflates a range of other cannabis use patterns (such as recency and frequency of use).

Cognitive performance failed to substantially differentiate cannabis users from non-users when recency of cannabis use was explored. In particular, those who met criteria for cannabis abuse/dependence in the past week performed significantly better than non-users on only one cognitive component, yet, the majority of participants who comprised the high frequency users described above performed better on at least one third of all cognitive components when compared to medium and low frequency users. Given that frequency of cannabis use was the only covariate entered in the logistic regression analyses for cannabis abuse/dependence in the past week, these results demonstrated that frequency of cannabis use is a stronger predictor of cognitive performance in Schizophrenia, to the extent that when it is controlled, differences between users and non-users fail to emerge.

Example 2: Administration of a cannabinoid or cannabinoid receptor agonist to individuals with Schizophrenia

The potential enhancing effects of cannabis on cognition in individuals suffering from Schizophrenia can be investigated in a randomised, double-blind, placebo controlled trial of either a cannabinoid or an agonist/partial agonist of cannabinoid receptors. Suitable compounds for use in the study include Nabilone and Sativex.

A study has been approved by the Northern Sydney Health Human Research Ethics Committee (Research Protocol 0401-023M (CTN): "The Effects of Cannabinoids on Cognition in Schizophrenia"). Participants: Inclusion I exclusion criteria

Participants in such a trial would include up to 30 individuals diagnosed with Schizophrenia or Schizoaffective Disorder. To be included in the research, participants would need to either have or be: i. A diagnosis of Schizophrenia or Schizoaffective Disorder according to DSM-IV criteria ii. Aged between 18 and 50 years iii. An estimated Premorbid IQ above 90 iv. Based in the community, proficient in the English language, and able to provide informed consent for participation v. A history of cannabis use without exacerbation of psychotic symptoms vi. Not used cannabis in the 6 month period prior to recruitment vii. Been psychiatrically stable for at least two weeks prior to enrolling in the study viii. No indication of current liver dysfunction, hypertension, or cardiac disease ix. No known history of neurological illness or acquired cerebral injury x. No history of developmental or intellectual disability xi. Not been dependent on alcohol or other substances in the six months prior to enrolment in the study xii. Not currently using opiates or benzodiazepines xiii. Not pregnant or breast feeding while participating in the study

Assessment in such a randomised, double-blind placebo controlled drug trial would pertain to psychiatric symptoms, drug and alcohol use, mood and anxiety, and cognitive functions in similar domains and using similar measures to those described in Example 1.

Participants would initially be screened for their suitability to participate in the study according to the above inclusion criteria and be provided an information and consent form. Baseline assessment would then be performed, entailing measurement of cognitive functions, substance use, psychiatric symptoms and mood/anxiety states. Following baseline assessment, participants would then be randomly allocated to either placebo or one of two treatment groups (low dose or high dose) on a daily basis for an ascertained period of time. The study investigators would remain blind as to which group participants were allocated. Depending on the compound employed in the study, the exact dosage(s) may be determined on an individual basis for each participant. For example, it may be appropriate to enable individual participants to titrate their own effective dose. Alternatively, by way of example, in the case of nabilone (which may be prepared in tablet/capsule form for oral ingestion), a low dose may be approximately 2mg riabilone/day and a high dose approximately 4mg nabilone/day. In the case of Sativex (which may be prepared as an oromucosal spray), a low and high dose may be determined by by the number of sprays per day (e.g., two and four sprays per day of the composition).

Re-assessment of participants would then take place when those allocated to the treatment groups were stabilised on the relevant dosage level. Re-assessment would involve re-measurement of cognitive functions, psychiatric symptoms, drug/alcohol use, and mood/anxiety symptoms.

All participants would be required to refrain from consuming alcohol or other recreational drugs during the treatment phase. A urine sample would be taken from participants at the time of each assessment to ensure compliance with treatment and non-use of recreational drugs. In addition, participants who had not had a routine blood test in the six month period preceding recruitment would have a blood test undertaken to screen for liver dysfunction, pregnancy, and cardiac disease. Any participant with indication of these would be excluded from the study.

During the treatment phase, the first 3 participants would need to be reviewed face-to-face every 24 hours by their treating mental health clinicians to establish safety of the drug. Pending the outcome of the first 3 participants, the remaining participants would need to be reviewed twice-weekly by their treating mental health clinicians. Participants who experienced exacerbation of psychotic symptoms, or any other adverse reaction after commencing treatment would immediately be withdrawn from the study. Psychiatric assessment would subsequently be organised and appropriate clinical management would follow (e.g., hospitalisation). Psychiatric assessment would also be organised for participants who decided to withdraw from the study. Participants would also be withdrawn from the study if recreational use/abuse of cannabis was suspected during the study.

Date analysis

The data would be analysed to determine if participants treated with the cannabinoid or cannabinoid receptor agonist demonstrated a significantly more reliable and/or clinically significant change in test scores than those on placebo.

Method of data analysis would be undertaken, for example, using a two-way repeated measures MANOVA, with dosage level as the between groups main factor and time of assessment (ie., baseline and treatment phase) as the repeated factor.

The following are to be construed as merely illustrative examples of compositions and not as a limitation of the scope of the present invention in any way.

Example 3(a): Capsule composition

A composition of a suitable agent or compound in the form of a capsule may be prepared by filling a standard two-piece hard gelatin capsule with 50 mg of the agent or compound, in powdered form, 100 mg of lactose, 35 mg of talc and 10 mg of magnesium stearate.

Example 3(b): Composition for inhalation administration

For an aerosol container with a capacity of 20-30 ml: a mixture of 10 mg of a suitable agent or compound with 0.5-0.8% by weight of a lubricating agent, such as polysorbate 85 or oleic acid, is dispersed in a propellant, such as freon, and put into an appropriate aerosol container for either intranasal or oral inhalation administration.

Example 3(c): Ointment composition

A typical composition for delivery as an ointment includes 1.Og of a suitable agent or compound, together with white soft paraffin to 100.0 g, dispersed to produce a smooth, homogeneous product. Example 3(d): Topical cream composition

A typical composition for delivery as a topical cream is outlined below: Suitable agent or compound 1.0 g Polawax GP 200 25.O g

Lanolin Anhydrous 3.0 g White Beeswax 4.5 g

Methyl hydroxybenzoate 0.1 g Deionised & sterilised Water to 100.0 g

The polawax, beeswax and lanolin are heated together at 60⁰C, a solution of methyl hydroxybenzoate is added and homogenisation achieved using high speed stirring. The temperature is then allowed to fall to 5O⁰C. The agent or compound is then added and dispersed throughout, and the composition is allowed to cool with slow speed stirring. Example 3(ø): Topical lotion composition

A typical composition for delivery as a topical lotion is outlined below: Suitable agent or compound 1.2 g Sorbitan Monolaurate 0.8 g Polysorbate 20 0.7 g

Cetostearyi Alcohol 1.5 g

Glycerin 7.0 g

Methyl Hydroxybenzoate 0.4 g Sterilised Water about to 100.00 ml The methyl hydroxybenzoate and glycerin are dissolved in 70 ml of the water at 75⁰C. The sorbitan monolaurate, polysorbate 20 and cetostearyi alcohol are melted together at 75⁰C and added to the aqueous solution. The resulting emulsion is homogenised, allowed to cool with continuous stirring and the agent or compound is added as a suspension in the remaining water. The whole suspension is stirred until homogenised. Example 3(f): Composition for parenteral administration

A composition for intramuscular injection could be prepared to contain 1 mL sterile buffered water, and 1 mg of a suitable agent or compound.

Similarly, a composition for intravenous infusion may comprise 250 ml of sterile Ringer's solution, and 5 mg of a suitable agent or compound. Example 3(g): Injectable parenteral composition

A composition suitable for administration by injection may be prepared by mixing 1% by weight of a suitable agent or compound in 10% by volume propylene glycol and water. The solution is sterilised by filtration.

Darby et al., 2002, Neurology 59:1042-1046 Delis et al., 2001, The Delis-Kaplan Executive Function System (D-KEFS). The Psychological Corporation: A Harcourt Assessment Company 3 Kongs et al., 2000, Wisconsin Card Sorting Test- Card Version (manual). Odessa, Florida: Psychological Assessment Resources

4 Rey, 1964, L 'examen Clinique en Psychologie. Paris: Presses Universitaires de France

5 Hooper, 1983, Hooper Visual Organisation Test. Los Angeles: Western Psychological Services

6 Gollin, 1960, Perceptual Motor Skills, 11:289-298

7 Warrington & James, 1991, Visual Object and Space Perception Battery. Suffolk, England: Thames Valley Test Co.

Perceptual Organisation I

Hooper Visual Organisation Test Square root (C-X) Low score = good performance

Gollm Incomplete Pictures Test High, score = good performance

VOSP Incomplete Letters Log 10 (C-X) Low score = good performance

VOSP Sillhouettes High score = good performance

VOSP Object Decisions High score = good performance

VOSP Progressive Silhouettes Square root (C-X) (Low score = good performance

C = Constant from which each score (X) was subtracted so that the smallest score was 1; required for measures that were negatively skewed

frequency users, therefore, not significant

Table 9 (cont'd)

Denotes components on which lower scores reflected better performance

Denotes statistical significance (i.e., p <0.002 according to Bonferroni adjustment

components)

Denotes approaching statistical significance (i.e., ρ≤D.05) ns Not significant * Alcohol use in the past month was entered as a covariate for this component

Two participants with non-dependent other illicit substance use in the past month were deleted from these components

Φ Two participants with other substance abuse/dependence in the past month were deleted from this component

Covariates for "High" vs "Low" analyses were cannabis abuse in the past month and lifetime cannabis abuse/dependence λ Covariates for "High" vs "Medium" analyses were cannabis abuse in the past month and non-dependent cannabis use in the past month

Covariates for "Medium" vs "Low" analyses were lifetime cannabis abuse/dependence and non-dependent cannabis use in the past month

Bold font denotes the subgroup which performed best on each component as yielded by logistic regression analyses

OJ

Claims

I . A method for improving cognitive functioning in an individual suffering from a neuropsychiatric disorder associated with impaired cognitive functioning, the method comprising administering to the individual a therapeutically effective amount of cannabis, or at least one extract or constituent thereof.

2. The method according to claim 1 wherein the neuropsychiatric disorder is Schizophrenia, Schizoaffective Disorder or a related disorder.

3. The method according to claim 1 wherein the neuropsychiatric disorder is Schizophrenia.

4. The method according to any one of the preceding claims wherein improvements in cognitive functioning comprise improvements in one or more of the following: attention and processing speed, executive functions, memory, perceptual organisation, motor skills, and emotional processing.

5. The method according to any one of the preceding claims wherein the at least one cannabis constituent is a natural or synthetic cannabinoid.

6. The method according to claim 5 wherein the cannabinoid is selected from the group consisting of: cannabidiol; Δ-9-tetrahydrocannabinol; Δ-8-tetrahydrocannabinol; cannabigerol; cannabichromene; cannabicycol; cannabielsoin; cannabinol; cannabinodiol; tetrahydrocannabinovarin; cannabidivarin; cannabadivarol; cannabinolic acid; olivetol; and cannabitriol.

7. The method according to claim 5 wherein the synthetic cannabinoid is nabilone, dronabinol, levonantradol, BRL-4664 or other suitable cannabinoid analogue.

8. The method according to any one of claims 1 to 4 wherein the at least one cannabis constituent is a cannflavin.

9. The method according to claim 8 wherein the cannflavin is selected from cannflavin A and cannflavin B.

10. The method according to any one of the preceding claims wherein two or more cannabis constituents are administered to the individual in a ratio sufficient to produce an improvement in cognitive functioning of the individual.

II. A method for improving cognitive functioning in an individual suffering from a neuropsychiatric disorder associated with impaired cognitive functioning, the method comprising administering to the individual a therapeutically effective amount of at least one agonist of a cannabinoid receptor.

12. The method according to claim 11 wherein the neuropsychiatric disorder is Schizophrenia, Schizoaffective Disorder or a related disorder.

13. The method according to claim 11 wherein the neuropsychiatric disorder is Schizophrenia.

14. The method according to any one of claims 11 to 13 wherein improvements in cognitive functioning comprise improvements in one or more of the following: attention and processing speed, executive functions, memory, perceptual organisation, motor skills, and emotional processing.

15. The method according to any one of claims 11 to 14 wherein the cannabinoid receptor is selected from the CB1 receptor and the CB2 receptor.

16. A pharmaceutical composition for improving cognitive functioning in an individual suffering from a neuropsychiatric disorder associated with impaired cognitive functioning, the composition comprising cannabis, or at least one extract or constituent thereof.

17. The composition according to claim 16 wherein the neuropsychiatric disorder is Schizophrenia, 5 Schizoaffective Disorder or a related disorder.

18. The composition according to claim 16 wherein the neuropsychiatric disorder is Schizophrenia.

19. The composition according to any one of claims 16 to 18 wherein improvements in cognitive functioning comprise improvements in one or more of the following: attention and processing speed, executive functions, memory, perceptual organisation, motor skills, and emotional processing. io

20. The composition according to any one of claims 16 to 19 wherein the composition comprises at least one cannabis extract.

21. The composition according to any one of claims 16 to 19 wherein the composition comprises at least one cannabis constituent.

22. The composition according to claim 21 wherein the at least one cannabis constituent is a natural i₅ or synthetic cannabinoid.

23. The composition according to claim 22 wherein the cannabinoid is selected from the group consisting of: cannabidiol; Δ-9-tetrahydrocannabinol; Δ-8-tetrahydrocannabinol; cannabigerol; cannabichromene; cannabicycol; cannabielsoin; cannabinol; cannabinodiol; tetrahydrocannabinovarin; cannabidivarin; cannabadivarol; cannabinolic acid; olivetol; and cannabitriol.

20 24. The composition according to claim 22 wherein the synthetic cannabinoid is nabilone, dronabinol, levonantradol, BRL-4664 or other suitable cannabinoid analogue.

25. The composition according to claim 21 wherein the at least one cannabis constituent is a cannflavin.

26. The composition according to claim 25 wherein the cannflavin is selected from cannflavin A and 2₅ cannflavin B.

27. The composition according to claim 21 wherein the composition comprises two or more cannabis constituents.

28. The composition according to claim 27 wherein the two or more cannabis constituents are in a ratio sufficient to produce an improvement in cognitive functioning when administered to an individual

30 suffering from a neuropsychiatric disorder associated with impaired cognitive functioning.

29. A pharmaceutical composition for improving cognitive functioning in an individual suffering from a neuropsychiatric disorder associated with impaired cognitive functioning, the composition comprising at least one agonist of a cannabinoid receptor.

30. The composition according to claim 29 wherein the neuropsychiatric disorder is Schizophrenia, 35 Schizoaffective Disorder or a related disorder.

31. The composition according to claim 29 wherein the neuropsychiatric disorder is Schizophrenia.

32. The composition according to any one of claims 29 to 31 wherein improvements in cognitive functioning comprise improvements in one or more of the following: attention and processing speed, executive functions, memory, perceptual organisation, motor skills, and emotional processing.

33. The composition according to any one of claims 29 to 32 wherein the cannabinoid receptor is selected from the CB 1 receptor and the CB2 receptor.

34. The use of an effective amount of cannabis, or at least one extract or constituent thereof for the manufacture of a medicament for improving cognitive functioning in an individual suffering from a neuropsychiatric disorder associated with impaired cognitive functioning.

35. The use of an effective amount of at least one agonist of a cannabinoid receptor for the manufacture of a medicament for improving cognitive functioning in an individual suffering from a neuropsychiatric disorder associated with impaired cognitive functioning.