Petitioner Mylan Pharmaceuticals Inc. - Exhibit 1019 - Page 1
`Petitioner Amerigen Pharmaceuticals Ltd.
`
`

`
`Petitioner Amerigen Pharmaceuticals Ltd.
`Petitioner Mylan Pharmaceuticals Inc. - Exhibit 1019 - Page 2
`
`

`
`Petitioner Mylan Pharmaceuticals Inc. - Exhibit 1019 - Page 3
`Petitioner Amerigen Pharmaceuticals Ltd.
`
`

`
`Petitioner Amerigen Pharmaceuticals Ltd.
`Petitioner Mylan Pharmaceuticals Inc. - Exhibit 1019 - Page 4
`
`

`
`Petitioner Amerigen Pharmaceuticals Ltd.
`Petitioner Mylan Pharmaceuticals Inc. - Exhibit 1019 - Page 5
`
`

`
`Petitioner Amerigen Pharmaceuticals Ltd.
`Petitioner Mylan Pharmaceuticals Inc. - Exhibit 1019 - Page 6
`
`

`
`C.A. Lipinski et al.
`
`/ Advanced Drug Delivery Re\'iew.r 23 (1997) 3-25
`
`thought should be globally associated with solubility
`and permeability; namely molecular weight; Log P;
`the number of H—bond donors and the number of
`
`H-bond acceptors. In a manner similar to setting the
`confidence level of an assay at 90 or 95% we asked
`how these four parameters needed to be set so that
`about 90% of the USAN compounds had parameters
`in a calculated range associated with better solubility
`or permeability. This analysis
`led to a
`simple
`mnemonic which we called the ‘rule of 5’
`[20]
`
`because the cutoffs for each of the four parameters
`were all close to 5 or a multiple of 5. In the USAN
`set we found that
`the sum of Ns and Os in the
`
`molecular formula was greater than 10 in 12% of the
`compounds. Eleven percent of compounds had a
`MWT of over 500. Ten percent of compounds had a
`CLogP larger than 5 (or an MLogP larger than 4.15)
`and in 8% of compounds the sum of OHS and NHs
`in the chemical structure was larger than 5. The ‘rule
`of 5’ states that: poor absorption or permeation are
`more likely when:
`
`There are more than 5 H—bond donors (expressed
`as the sum of OHs and NHs);
`The MWT is over 500;
`
`The Log P is over 5 (or MLogP is over 4.15);
`There are more than 10 H—bond acceptors (ex-
`pressed as the sum of Ns and Os)
`Compound classes that are substrates for bio-
`logical transporters are exceptions to the rule.
`
`When we examined combinations of any two of
`the four parameters in the USAN data set, we found
`that combinations of two parameters outside the
`desirable range did not exceed 10%. The exact
`values from the USAN set are:
`sum of N and
`0+ sum of NH and OH — 10%; sum of N and
`O + MWT —- 7%; sum of NH and OH + MWT —
`
`4% and sum of MWT+ Log P — 1%. The rarity
`(1%) among USAN drugs of the combination of
`high MWT and high log P was striking because this
`particular combination of physico—chemical proper-
`
`ties in the USAN list
`
`is enhanced in the leads
`
`resulting from high throughput screening.
`The rule of 5 is now implemented in our registra-
`tion system for new compounds synthesized in our
`medicinal chemistry laboratories and the calculation
`program runs automatically as the chemist registers a
`new compound. If two parameters are out of range, a
`‘poor absorption or permeability is possible’ alert
`appears on the registration screen. All new com-
`pounds are registered and so the alert
`is a very
`visible educational tool for the chemist and serves as
`
`for the research organization. No
`a tracking tool
`chemist
`is prevented from registering a compound
`because of the alert calculation.
`
`2. 7. Orally active drugs outside the ‘rule of 5’
`mnemonic and biologic trarisporters
`
`The ‘rule of 5’
`
`is based on a distribution of
`
`calculated properties among several thousand drugs.
`Therefore by definition, some drugs will lie outside
`the parameter cutoffs in the rule. Interestingly, only a
`small number of therapeutic categories account for
`most of the USAN drugs with properties falling
`outside our parameter cutoffs. These orally active
`therapeutic classes outside the
`‘rule of 5'
`are:
`antibiotics. antifungals. vitamins and cardiac glyco-
`sides. We suggest that these few therapeutic classes
`contain orally active drugs that violate the ‘rule of 5’
`because members of these classes have structural
`
`features that allow the drugs to act as substrates for
`naturally occurring transporters. When the ‘rule of 5‘
`is modified to exclude these few drug categories only
`a very few exceptions can be found. For example.
`among the NCEs between 1990 and 1993 falling
`outside the double cutoffs in ‘the rule of 5’.
`there
`
`were nine non—orally active drugs and the only orally
`active compounds outside the double cutoffs were
`seven antibiotics. Fungicides-protoazocides—antisep-
`tics also fall outside the rule. For example, among
`the 41 USAN drugs with MWT > 500 and MLogP >
`4.15 there were nine drugs in this class. Vitamins are
`another orally active class drug with parameter
`values outside the double cutoffs. Close to l0()
`
`into this category. Cardiac glycosides.
`vitamins fell
`an orally active drug class also fall outside the
`parameter limits of the rule of 5. For example among
`90 USANS with high MWT and low MLogP there
`were two cardiac glycosides.
`
`Petitioner Mylan Pharmaceuticals Inc. - Exhibit 1019 - Page 7
`Petitioner Mylan Pharmaceuticals Inc. — Exhibit 1019 — Page 7
`
`

`
`10
`
`CA. Ll])lIl.\'l(l et ul.
`
`/ Atl\'(im'ezl Drug [)eliverj\‘ Ré’\'l£’H‘.Y 2.? (I997) .?»25
`
`2.8. High MWT USANX and the trend in MLogP
`
`l)rugs in absorption and permeability
`2.10.
`studies. calculations
`
`In our USAN data set we plotted MLogP against
`MWT and examined the compound distributions as
`defined by the 50 and 90% probability ellipses. A
`large number of USAN compounds had MLogP
`more negative than ~ 0.5. Among the USAN com-
`pounds
`there was
`a trend for higher MWT to
`correlate with lower MLogP. This type of trend is
`distinctly different
`from the positive correlation
`between MLogP and MWT found in most SAR data
`sets. Usually as MWT increases. compound lipo-
`philicity increases and MLogP becomes larger (more
`positive). From among the 264i USANs. we selected
`the 405 with MLogP more negative than — ().5 and
`from among these selected those with MWT in
`excess of 500 and mapped the resulting 90 against
`therapeutic activity fields
`in
`the MACCS WDI
`database. About one half (44 of 90) of these high
`MWT,
`low MLogP USANs were orally inactive
`consisting of 26 peptide agonists or antagonists. ll
`quaternary ammonium salts and seven miscellaneous
`non-orally active agents.
`Among the USAN compounds in our list fewer
`than 10% of compounds had either high MLogP or
`high MWT. The combination of both these prop-
`erties in the same compound was even rarer. Among
`264] USANs there were only 41 drugs with MWT >
`500 and MLogP>4.15. about one-half (21) were
`orally inactive. Among the remainder there were
`only six orally active compounds not in the fungicide
`and vitamin classes.
`
`2.9. New chentieal entities. eczl(rulation.s'
`
`New chemical entities introduced between 1990
`
`and 1993 were identified from a summary listing in
`vol. 29 of Annual Reports in Medicinal Chemistry.
`All our computer programs for calculating physico—
`chemical properties require that
`the compound be
`described in computer—readable format. We mapped
`compound names and used structural searches to
`identify 133 of the NCEs in the Derwent World Drug
`to give us the computer—readable formats to calculate
`the rule of 5. The means of calculated properties
`were well within the acceptable range. The average
`Moriguchi log P was 1.80, the sum of H-bond donors
`was 2.53, the molecular weight was 408 and the sum
`of Ns and Os was 6.95. The incidence of alerts for
`
`possible poor absorption or permeation was 12%.
`
`Very biased data sets are encountered in the types
`of drugs that are reported in the absorption or
`permeability literature. Calculated properties
`are
`quite favorable when compared to the profiles of
`compounds detected by high throughput screening.
`Compounds that are studied are usually orally active
`marketed drugs and therefore by definition have
`properties within the acceptable range. What
`is
`generally not appreciated is
`that absorption and
`permeability are mostly reported for the older drugs.
`For example, our list of compounds with published
`literature on absorption or permeability,
`studied
`internally for validation purposes,
`is highly biased
`against NCEs. Only one drug in our list of 73 was
`introduced in the period 1990 to date.
`In part this
`reflects drug availability. since drugs under patent
`are not
`sold by third parties. Drugs
`studied in
`absorption or permeability models tend to be those
`with value for assay validation purposes,
`i.e.
`those
`with considerable preexisting literature. In addition.
`some of the newer studies are driven by a regulatory
`agency interest
`in the permeability properties of
`generic drugs.
`In our listing of 73 drugs in absorp-
`tion or permeability studies there are 33 generic
`drugs whose properties the FDA is currently profil-
`ing. Our list
`includes an additional 23 drugs with
`CACO—2 cell permeation data. Most of these are
`lrom the speakers’ handouts at a recent meeting on
`permeation prediction I21]; a few are from internal
`Pfizer CACO—2 studies. A final
`I2 drugs are those
`with zwitterionic or very hydrophilic properties for
`which there are either literature citations or internal
`
`Pfizer data. The means of calculated properties for
`compounds in this list are well within the acceptable
`range. The average Moriguchi
`log P was 1.60.
`the
`sum of H—bond donors was 2.49.
`the molecular
`
`weight was 361 and the sum of Ns and Os was 6.27.
`The incidence of alerts for possible poor absorption
`or permeation was l2“/o (Table 1).
`
`2.] /. Validating the computational alert
`
`Validating a computational alert for poor absorp-
`tion or permeation in a discovery setting is quite
`different
`than validating a quantitative prediction
`calculation in a developmental setting.
`In effect, a
`discovery alert is a very coarse filter that identifies
`
`Petitioner Mylan Pharmaceuticals Inc. - Exhibit 1019 - Page 8
`Petitioner Mylan Pharmaceuticals Inc. — Exhibit 1019 — Page 8
`
`

`
`3:("D::
`
`O0--C—CCOCO-—C©<3<DCD©C<3C'—-COCO
`
`C.A. Lipinski er al.
`
`/ Advanced Drug Delivery Reviews 23 (I997) 3-25
`
`Table 1
`
`Partial list of drugs in absorption and permeability studies
`
`MWT
`225.21
`308.77
`180.16
`266.34
`749.00
`267.25
`334.40
`194.19
`515.65
`217.29
`236.28
`323.14
`252.34
`230.10
`1202.64
`266.39
`392.47
`284.75
`296.15
`414.53
`543.53
`376.46
`733.95
`337.45
`384.26
`130.08
`244.27
`330.75
`75.07
`297.74
`206.29
`280.42
`705.65
`380.92
`254.29
`328.42
`405.50
`182.18
`454.45
`267.37
`309.41
`327.38
`230.27
`263.39
`267.25
`451.49
`331.35
`383.41
`259.35
`324.43
`314.41
`303.36
`320.76
`471.69
`288.43
`416.36
`144.22
`81 1.00
`412.95
`
`—DJ'—‘LoJ'—‘I‘JfJ"‘l\)'—I\)l\3I‘J|~)I\J'——l\)-‘3IJ\]g‘C/1K/1*‘OOC'—‘-KCAJ-53'—‘f\)'—XLIIf\7\)O'\’oLI~)'—‘LI'Il\JLrJQ\JT\)—TJOl\)Y\)5J1-I3'—‘$§
`
`MLOgP
`Drug name
`~ 0.09
`Acic1ovir""‘
`4.74
`Alprazolam"
`1.70
`Aspirinh
`0.92
`Atenolol”
`0.14
`Azithromycinh
`- 4.38
`AZT“
`1.82
`Benz)/I—penici11in"
`0.20
`Caffeine"
`3.03
`Candoxatril"
`0.64
`Captopril“
`3.53
`Carbamazepine"
`1.23
`Chloramphenicolh
`0.82
`C1I'I'IC[id1ne~'.h
`3.47
`Clonidine"
`—0.32
`Cyclosporine"
`3.64
`Desipramine”
`1.85
`Dexamethzisone"
`3.36
`Diazepamh
`3.99
`Diclofenac“
`2.67
`DiltiaZem—HC1"
`— 1.33
`Doxorubicin"
`1 .64
`Ena1apri1—maleate“
`~0.14
`Erythromycin“
`— 0.18
`Famotidine"
`3.22
`Felodipine”
`-0.63
`Fluorouraci 1 "
`3.90
`Flurbiprofen"
`0.95
`Fu['OS61Tl1idC“
`- 3.44
`Glycine ‘
`— 1.08
`1-Iydrochlorthiuzide"
`3.23
`Ibuprofen“
`3.88
`Imipramine"
`5.53
`ltraconazole"
`4.45
`Ketaconazole"
`3.37
`Ketoprofen“
`2.67
`Labetz1lol—HC|“
`1.1 1
`Lisinopril"
`A 2.50
`Mannitolh
`1 .60
`Methotrexute"
`I .65
`Metopro1o1—tartrateM
`0.97
`Nadolol"
`1.53
`Naloxone“
`2.76
`Naproxen—sodium""'
`4.14
`Nortriptylene-HC1"
`— 4.38
`Omeprazole"
`2.20
`Phenytoin“
`0.00
`Piroxiczim"
`2.05
`Prazosinh
`2.53
`Proprunolo1—HCl“‘"
`2.19
`Quinidine"
`0.66
`Ranitidine—HC1"
`1 .42
`Scopolamine"
`I .95
`Tenidaph
`4.94
`Terfenadine"
`3.70
`Testosterone"
`2.81
`Trovafloxucin"
`2.06
`Valproic—zicid"
`2.96
`Vinblastineh
`3.71
`Ziprusidone"
`"Standard or drug in FDA bioequivalence study.
`“Studied in CACO-2 permeation.
`"Sum of OH and NH H—bond donors.
`“Sum of N and O 1-l—bond acceptors.
`“Computational alert according to the rule of 5; 0. no problem detected; 1, poor absorption or permeation are more likely.
`
`2 + 0.
`
`'—ta\l3\'>—LNLIIU1-I3’.rJC7\OGL)1bd--IJI\)t\)\12r-J\IlJ-I331\C<FA\lI\)C!\’JJ'.»)UII\J'4J§»JO‘\lUJ¥3$O‘O‘45-Iékll-P-5300
`
`’Ji:lJ\lrJ'.aJ'Ji’.I1\l-5>’.aJ\C
`
`Petitioner Mylan Pharmaceuticals Inc. - Exhibit 1019 - Page 9
`Petitioner Mylan Pharmaceuticals Inc. — Exhibit 1019 — Page 9
`
`

`
`1')
`-
`
`(IA. LI"/1iI1.\‘/ti
`
`()1 ul.
`
`/ Ac/vuimul [hug [)6/i1'w'_\' Rz*\'irIw.\' 2.? ([997) 3-25
`
`compounds lying in a region of property space where
`the probability of useful oral activity is very low.
`The goal
`is to move chemistry SAR towards the
`region of property space where oral activity is
`reasonably possible (but not assured) and where the
`more labor-intensive techniques of drug metabolism
`and the pharmaceutical sciences can be more elli-
`ciently employed. A compound that fails the compu-
`tational alert will
`likely be poorly bio—available
`because of poor absorption or permeation and lies
`within that
`region of property space where good
`absorption or solubility is unlikely. We believe the
`alert has its primary value in identifying problem
`compounds.
`In our experience,
`tnost compounds
`failing the alert also will prove troublesome if they
`progress far enough to be studied experimentally.
`However.
`the converse is not
`true. Compounds
`passing the alert
`still can prove troublesome in
`experimental studies.
`In this perspective. a useful computational alert
`correctly identifies drug projects with known absorp-
`tion problems. Drugs
`in human therapy, whether
`poorly or well absorbed from the viewpoint of the
`pharmaceutical scientist. should profile as
`‘drugs‘.
`i.e.
`having reasonable prospects for oral activity.
`The larger the computational and experimental dif-
`ference between drugs in human therapy and those
`which are currently being made in medicinal chemis-
`try laboratories,
`the greater the confidence that
`the
`differences are meaningful. We assert that absorption
`problems have recently become worse in the pharma-
`ceutical
`industry as attested to by recent meetings
`and symposia on this
`subject
`[22] and by the
`informal but
`industry—wide concern of pharmaceu-
`tical scientists about drug candidates with less than
`optimal physical properties. If we are correct. within
`any drug organization. one should be able to quantify
`by calculation whether time-dependent changes that
`might impair absorption have occurred in medicinal
`chemistry.
`if these changes have occurred one can
`try to correlate these with changes in screening
`strategy.
`
`2.12. Changes in ('(l/('ll[(lT€(/
`])I‘0fi[(’.\‘ (If P/lZ(’l‘
`
`[7l1_\‘.s'iml property
`
`the Pfizer
`is our experience at
`How relevant
`Central Research laboratories in Groton to what may
`be expected to be observed in other drug discovery
`
`organizations‘? The physical property profiles of drug
`leads discovered through HTS will be similar indus-
`try—wide
`to the extent
`that
`testing methodology,
`selection criteria and the compounds being screened
`are similar. Changes in physical property profiles of
`synthetic compounds, made in follow—up of HTS
`leads by medicinal
`laboratories, depend on the
`timing of a major change towards HTS screening.
`The Pfizer laboratories in Groton were one of the
`
`lirst to realize and implement the benefits of HTS in
`lead detection. As a consequence. we also have been
`one of the first to deal with the effects of this change
`in screening strategy on physico-chemical properties.
`in Groton. 1989 marked the beginning of a signifi-
`cant change towards HTS screening. This process
`was largely completed by 1992 and currently HTS is
`now the major, rich source of drug discovery leads
`and has largely supplanted the pre~l989 pattern of
`lead generation.
`At the Pfizer Groton site, we have retrospectively
`examined the MWT distributions of compounds
`made in the pre—l989 era and since 1989. Since our
`registration systems unambiguously identify the
`source of each compound, we can identify any time-
`dependent change in physical properties and we can
`compare the profiles of internally synthesized com-
`pounds with the profiles of compounds purchased
`from external commercial sources.
`
`the percentage of internally syn-
`Before 1989.
`thesized high MWT compounds oscillated in a range
`very similar to the USAN library (Table 2). Starting
`in 1989. there was an upward jump in the percentage
`of high MWT compounds and a furtherjump in 1992
`to a new stable MWT plateau that is higher than in
`
`Table 2
`
`Percent of compounds with MWT (including salt) above 500
`
`Year registered
`Pre— I 984
`l 98-1
`I985
`I980
`l 087
`1988
`I 98‘)
`1990
`l 9‘) l
`I992
`1993
`I 994
`
`Synthetic compounds Commercial compounds
`I6.()
`5.4
`18.9
`14.7
`l2.l
`l5.5
`126
`5.5
`I 3.4
`5.8
`14.6
`8.2
`23.4
`4.]
`2| .
`l
`3.3
`25.4
`l .8
`34.2
`6.8
`33.2
`8.4
`32.7
`7.‘)
`
`Petitioner Mylan Pharmaceuticals Inc. - Exhibit 1019 - Page 10
`Petitioner Mylan Pharmaceuticals Inc. — Exhibit 1019 — Page 10
`
`

`
`C.A. Lipinski er al.
`
`I Advanyed Drug Delivery Reviews 23 (1997) 3—25
`
`13
`
`the USAN library and higher than any yearly oscilla-
`tion in the pre—l989 era. By contrast, there was no
`change in the MWT profiles of commercially pur-
`chased compounds over the same time period. A
`comparison of the MWT and MLogP percentiles of
`synthetic compounds for a year before the advent of
`HTS and for 1994 in the post-HTS era shows a
`similar pattern (Table 3). The upper range percen-
`tiles for MWT and MLogP properties are skewed
`towards physical properties less favorable for oral
`absorption in the more recent time period.
`The trend towards higher MWT and LogP is in the
`direction of the property mix that is least populated
`in the USAN library. There was no change over time
`in the population of compounds with high numbers
`of H-bond donors or acceptors.
`
`2.13. The rationale for measuring drug solubility
`in a dismverjv setting
`
`In recent years, we have been exploring ex-
`perimental protocols
`in a discovery setting that
`measure drug solubility in a manner as close as
`possible to the actual solubilization process used in
`our biological laboratories. The rationale is that the
`physical forms of the compounds solubilized and the
`methods used to solubilize compounds in discovery
`are very different from those used by our pharma-
`ceutical scientists and that mimicking the discovery
`process will
`lead to the best prediction of in vivo
`SAR.
`
`the focus is on keeping a drug
`In discovery,
`solubilized for an assay rather than on determining
`the solubility limit. Moreover,
`there is no known
`automated methodology that can efficiently solubil-
`ize hundreds of thousands of sometimes very poorly
`soluble compounds under thermodynamic conditions.
`In our biological
`laboratories, compounds that are
`not obviously soluble in water or by pH adjustment
`
`Table 3
`
`Synthetic compound properties in 1986 (pre-HTS) and 1994
`(post-HTS)
`
`Percentile
`
`MLogP
`I 986
`
`4.30
`3.48
`2.60
`
`1994
`
`4.76
`3.90
`2.86
`
`MWT
`I986
`
`514
`415
`352
`
`are pre-dissolved in a water miscible solvent (most
`often DMSO) and then added to a well stirred
`aqueous medium. The equivalent of a thermody-
`namic solubilization, i.e. equilibrating a solid com-
`pound for 24-48 h, separating the phases, measuring
`the soluble aqueous concentration and then using the
`aqueous in an assay,
`is not done. When compounds
`are diluted into aqueous media from a DMSO stock
`solution, the apparent solubility is largely kinetically
`driven. The influence of crystal lattice energy and the
`effect of polymorphic forms on solubility is, of
`course, completely lost
`in the DMSO dissolution
`process. Drug added in DMSO solution to an aque-
`ous medium is delivered in a very high energy state
`which enhances the apparent solubility. The appear-
`ance of precipitate (if any) from a thermodynamical-
`ly supersaturated solution is kinetically determined
`and to our knowledge is not predictable by computa-
`tional methods. Solubility may also be perturbed
`from the true thermodynamic value in purely aque-
`ous media by the presence of a low level of residual
`DMSO.
`
`The physical form of the first experimental lot of a
`compound made in a medicinal chemistry lab can be
`very different from that seen by the pharmaceutical
`scientist at a later stage of development. Solution
`spectra, HPLC purity criteria and mass
`spectral
`analysis are quite adequate to support a structural
`assignment when the chemist’s priority is on effi—
`ciently making as many well selected compounds as
`possible in sufficient quantity for in vitro and in vivo
`screening. All the measurements that support struc-
`tural assignment are unaffected by the energy state
`(polymorphic form) of the solid. Indeed, depending
`on the therapeutic area, samples may not be crys-
`talline and most compounds synthesized for the first
`time are unlikely to be in lower energy crystalline
`forms. Attempts to compute solubility using melting
`point
`information are not useful
`if samples do not
`have well defined melting points. Well characterized,
`low energy physical
`form (from a pharmaceutics
`viewpoint)
`reduces aqueous
`solubility and may
`actually be counter productive to the discovery
`chemists priority of detecting in vivo SAR.
`In this setting, thermodynamic solubility data can
`be overly pessimistic and may mislead the chemist
`who is trying to relate chemical structural changes to
`absorption and oral activity in the primary in vivo
`assay. Our goal is to provide a relevant experimental
`
`Petitioner Mylan Pharmaceuticals Inc. - Exhibit 1019 - Page 11
`Petitioner Mylan Pharmaceuticals Inc. — Exhibit 1019 — Page 11
`
`

`
`I4
`
`CA. Lipinski er til.
`
`1 Atfwm<'ed Drug Delivery Reviews 23' (1997) 3—25
`
`solubility measurement so that chemistry can move
`from the pool of poorly soluble, orally inactive
`compounds towards those with some degree of oral
`activity. For maximum relevance to the in vivo
`biological assay our solubility measurement protocol
`is as close as possible to the biological assay
`‘solubilization’. In this paradigm, any problems that
`might be related to the poor absorption of a low
`energy crystalline solid under thermodynamic con
`ditions are postponed and not solved. The efficiency
`gain in an early discovery stage solubility assay lies
`in the SAR direction provided to chemistry and in
`the more efficient application of drug metabolism
`and pharmaceutical
`sciences
`resources once oral
`activity is detected. The value of this type of assay is
`very stage-dependent and the discovery type of assay
`is not a replacement for a thermodynamic solubility
`measurement at a later stage in the discovery pro-
`cess.
`
`2. I4. Drugs have high rurbidiinetm‘ solubility
`
`Measuring solubility by turbidimetry violates al—
`most every precept
`taught
`in the pharmaceutical
`sciences about
`‘proper’
`thermodynamic solubility
`measurement. Accordingly, we have been profiling
`known marketed drugs since our initial presentation
`on turbidimetric solubility measurement
`[23] and
`have measured turbidimetric solubilities on over 350
`
`drugs from among those listed in the Derwent World
`Drug Index. The calculated properties of these drugs
`are well within the favorable range for oral absorp-
`tion. The average of the calculated properties are:
`MLogP, 1.79; the sum of OH and NH, 2.01; MWT.
`295.4; the sum of N and O. 4.69. Without regard to
`the therapeutic class, only 4% of these drugs would
`have been flagged as having an increased probability
`of poor absorption or permeability in our computa-
`tional alert. Of the 353 drugs, 305 (87%) had a
`turbidimetric solubility of greater than 65 p.g/ml.
`There were only 20 drugs (7%) with a turbidimetric
`solubility of 20 pg/ml or
`less.
`If
`turbidimetric
`solubility values lie in this low range, we suggest to
`our chemists
`that
`the probability of useful oral
`activity is very low unless the compound is unusual-
`ly potent (e.g. projected clinical dose of 0.1 mg/kg)
`or unusually permeable (top tenth percentile in
`absorption rate constant) or unless the compound is a
`
`is a substrate for a
`
`member of a drug class that
`biological transporter.
`regard to
`Our drug list was compiled without
`literature thermodynamic solubilities but does con-
`tain many of the types of compounds studied in the
`absorption literature. Of the 353 drugs studied in the
`discovery solubility assay, l7l are drugs from four
`sources. There are '3? drugs from the compilation of
`200 drugs by Andrews et al. [6]. This compilation is
`biased towards drugs with reliable measured in vitro
`receptor affinity and with interesting functionality
`and not necessarily towards drugs with good absorp-
`tion or permeation characteristics. There are 23 drugs
`from a list of generics whose properties FDA is
`currently profiling for bio—equivalency standards.
`In
`addition.
`there are 42 NCES introduced between
`
`I983 and 1993 and 37 entries are for drugs with
`CACO—2 cell permeation data.
`The profile of drug turbidimetric solubilities serves
`as a useful benchmark. Compounds that are drugs
`have a very low computational alert rate for absorp-
`tion or permeability problems and a low measured
`incidence of poor turbidimetric solubility of about
`10%. The calculated profiles and alert
`rates of
`compounds made in medicinal chemistry laboratories
`can be compared to those of drugs and the profiles
`can be compared on a project by project basis.
`Within the physical property manifold of ‘mar-
`keted drugs’ we would expect a poor correlation of
`our
`turbidimetric
`solubility data with literature
`thermodynamic solubility data since the properties of
`‘drugs' occupy only a small region of property space
`relative to what is possible in synthetic compounds
`and HTS ‘hits’. Our turbidimetric solubilities for
`
`the top end of a
`drugs are almost entirely at
`relatively narrow solubility range, whereas from a
`thermodynamic viewpoint the drugs in our list cover
`a wide spectrum of solubility. We caution that
`turbidimetric solubility measurements are most defi-
`nitely not a substitute for careful
`thermodynamic
`solubility measurements on well characterized crys-
`talline drugs and should not be used for decision
`making in a development setting.
`
`2.15. High throughput srrreening hits, c'alCulati0rz.s'
`and solubilizy mea.mremem.s'
`
`Calculated properties and measured turbidimetric
`solubilities for
`the best compounds
`identified as
`
`Petitioner Mylan Pharmaceuticals Inc. - Exhibit 1019 - Page 12
`Petitioner Mylan Pharmaceuticals Inc. — Exhibit 1019 — Page 12
`
`

`
`CA. Lipinski er al.
`
`/ Adm/mid Drug Deliverv R(7l’l(.’W.\‘ 23 (1997) 3—25
`
`l5
`
`‘hits‘
`
`in our HTS screens are in accord with the
`
`hypothesis that the physico—chemical profiles of leads
`have changes from those in the pre—l989 time period.
`Nearly 100 of the most potent ‘hits’ from our high
`throughput screens were examined computationally
`and their turbidimetric solubilitles were measured.
`
`The profiles are strikingly different from those of the
`353 drugs we studied. The HTS hits are on average
`more lipophilic and less soluble than the drugs. The
`96 compounds we measured were the end product of
`detection in HTS screens and secondary in vitro
`evaluation. These were the compounds highlighted in
`summaries and which captured the chemist’s interest
`with many IC50s clustered in the l p.M range. As
`such.
`they are the product of a biological
`testing
`process and a chemistry evaluation as to interesting
`subject matter. Average MLogP for the HTS hits was
`a full
`log unit higher than for the drugs and the
`average MWT was nearly 50 Da higher. By contrast,
`there was little difference in the number of hydrogen
`bond donors and acceptors. The distribution curves
`for MLogP and MWT are roughly the same shape
`for the HTS hits and drugs but the means are shifted
`upwards in the HTS hits with a higher distribution of
`compounds
`towards
`the
`unfavorable
`range of
`physico-chemical properties. The actual averages,
`HTS vs. Drug are: MLogP, 2.81 vs. 1.79; MWT, 366
`vs. 295; sum of OH NH, l.8O vs. 2.01; sum of N and
`O. 5.4 vs. 4.69.
`
`2.16. The triad of potency, solubility and
`permeability
`
`Acceptable drug absorption depends on the triad
`of dose. solubility and permeability. Our computa-
`tional alert does not factor in dose, i.e. drug potency.
`It only addresses properties
`that are related to
`potential solubility and permeation problems and it
`does not allow for a very favorable value of one
`parameter to compensate for a less favorable value of
`another parameter.
`In a successful marketed drug,
`one parameter can compensate for another. For
`example, a computational alert
`is calculated for
`azithromycin, a successful marketed antibiotic.
`In
`azithromycin, which has excellent oral activity, a
`very high aqueous solubility of 50 mg/ml more than
`counterbalances a very low absorption rate in the rat
`intestinal loop of 0.001 minfl. Poorer permeability
`in orally active peptidic-like drugs is usually com-
`
`pensated by very high solubility. Our solubility
`guidelines
`to our chemists
`suggest a minimum
`thermodynamic solubility of 50 ug/ ml for a com-
`pound that has a mid-range permeability and an
`average potency of 1.0 mg/kg. These solubility
`guidelines would be markedly higher if the average
`compound had low permeability.
`
`2.17. Protocols for measuring drug solubility in a
`discovery setting
`
`The method and timing of introduction of the drug
`into the aqueous media are key elements in our
`discovery solubility protocol. Drug is dissolved in
`DMSO at a concentration of 10 ug/p.l of DMSO
`which is close to the 30 mM DMSO stock con-
`
`centration used in our own biology laboratories. This
`is added a microlitre at a time to a non-chloride
`
`containing pH 7 phosphate buffer at room tempera-
`ture. The decision to avoid the presence of chloride
`was a tradeoff between two opposing considerations.
`Biology laboratories with requirements for iso-os-
`motic media use vehicles containing physiological
`levels of saline (e.g. Dulbecco’s phosphate buffered
`saline) with the indirect result that the solubility of
`HCl salts (by far the most frequent amine salt from
`our chemistry laboratories) can be depressed by the
`common ion effect. Counter to this consideration, is
`the near 100% success rate of our pharmaceutical
`groups in replacing problematical HCI salts with
`other salts not subject
`to a chloride common ion
`
`effect. We chose the non-chloride containing medium
`to avoid pessimistic solubility values resulting from a
`historically very solvable problem.
`The appearance of precipitate is kinetically driven
`and so we avoid a short
`time course experiment
`where we might miss precipitation that occurs on the
`type of time scale that would affect a biological
`experiment. The additions of DMSO are spaced a
`minute apart. A total of I4 additions are made. These
`correspond to solubility increments of < 5 ug/ ml to
`a top value of >65 p.g/ml if the buffer volume is
`2.5 ml
`(as
`in a UV cuvette).
`If it
`is clear that
`
`precipitation is occurring early in the addition se-
`quence, we stop the addition so that we have two
`consecutive readings after
`the precipitate is
`first
`detected. Precipitation can be quantified by an ab-
`sorbance increase due to light scattering by precipi—
`tated particulate material in a dedicated diode array
`
`Petitioner Mylan Pharmaceuticals Inc. - Exhibit 1019 - Page 13
`Petitioner Mylan Pharmaceuticals Inc. — Exhibit 1019 — Page 13
`
`

`
`16
`
`CA. Lipiiiski er ul.
`
`/ Advanced Drug [)eliv£r_v Reviews 23 (1997) 3-25
`
`UV machine. The sensitivity to light scattering is a
`function of the placement of the diode array detector
`relative to the cuvette and differs among instruments.
`We found that
`the array placement
`in a Hewlett
`Packard HP8452A diode array gives high sensitivity
`to light scattering. Increased UV absorbance from
`light scattering is measured in the 600-820 nm range
`because most drugs have UV absorbance well below
`this range.
`the precipitation
`implementation,
`In its simplest
`point
`is calculated from a bilinear curve fit
`to the
`Absorbance ( y axis) vs. ptl of DMSO (x axis) plot.
`The coordinates of the intersect point of the two line
`segments are termed X crit and Y crit. X crit is the
`microlitres of DMSO added when precipitation
`occurs and Y crit
`is
`the UV Absorbance at
`the
`
`precipitation point. The concentration of drug in
`DMSO (10 pug/ml)
`is known. The volume of
`aqueous buffer (typically 25 ml
`in a cuvette)
`is
`known so the drug concentration expressed as ug of
`drug per ml buffer at the precipitation point is readily
`calculated. The volume percent aqueous DMSO at
`the precipitation point
`is also reported. Under our
`assay conditions it does not exceed 0.67% for a
`turbidimetric solubility of >65 pg/ml. The upper
`solubility limit is based on the premise that for most
`projects permeability is not a major problem and that
`solubility assays will most often be requested for
`poorly soluble compounds.
`In the absence of poor
`permeability, solubilities above 65 pg/ml suggest
`that if bio-availability is poor, solubility is not the
`problem.
`
`2.18. Technical considerations and signal
`processing
`
`In our experience, most UV active compounds
`made in our Medicinal