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aem-Grid--default--12","appliedCssClassNames":"snowflake-layout-container-inner-padding-small",":items":{"blog_text":{"id":"blog-text-2c5750829a","text":"\u003Cp\u003Eライフサイエンス業界はデータに基づいて動いています。臨床試験の結果、規制当局への提出書類、製造品質記録、患者アウトカム、サプライチェーンのトレーサビリティなど、これらは単なる業務上の資産ではありません。市場に出回るすべての製品の科学的および商業的な基盤となるものです。このことが、M&Aや事業売却を非常に複雑なものにしています。大手製薬会社がバイオテクノロジー企業を買収する場合、獲得するのは知的財産や人員だけではありません。長年の研究、臨床データ、検証済みシステム、規制履歴、そしてそれらに伴うコンプライアンス義務も引き継ぐことになります。企業がビジネスユニットをスピンオフする際には、何十年にもわたって混在してきたデータを、多くの場合、規制や法律に基づく厳しいスケジュールの下で慎重に分離する必要があります。\u003C/p\u003E\n\u003Cp\u003Eこの課題に対する従来のアプローチは、時間がかかり、非常に高額なコストが発生する可能性があります。Snowflakeを活用することで、組織は最も価値のあるデータ資産を保護しながら、これらのスケジュールを最小限に抑えることができます。 \u003C/p\u003E\n\u003Ch3\u003Eライフサイエンス業界のM&Aにおけるデータの課題\u003C/h3\u003E\n\u003Cp\u003Eほとんどの企業は、実際に取引を開始するまで、データの複雑さを過小評価しています。企業が直面する課題の中には、ライフサイエンス業界特有のものがあります。\u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E規制の継続性：\u003C/b\u003E臨床試験記録、有害事象報告、是正措置・予防措置（CAPA）文書などの創薬データは、移行期間中も損なわれない状態を保ち、アクセス可能である必要があります。2つの企業が統合中であっても、FDAの査察が中断されることはありません。Good Practice（GxP）の検証済みシステムは、文書化、検証プロトコル、変更管理なしに単に移行することはできません。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E患者データとプライバシー義務：\u003C/b\u003E米国のHIPAA、欧州のGDPR、そして増加し続ける地域ごとのプライバシー規制により、患者レベルのデータを組織間で自由に移動させることはできません。統合または分離の際には、各データ転送の法的根拠を確立し、文書化する必要があります。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003Eデータリネージと科学的来歴：\u003C/b\u003E臨床データや製造データは、そのコンテキストと結びついて初めて意味を持ちます。機器、アナリスト、ロット番号、プロトコルに関するメタデータのないバイオアッセイ結果は、科学的価値がないだけでなく、規制上のリスクとなる可能性もあります。リネージを保持せずにデータを移動することは、許容される選択肢ではありません。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E長期にわたるデータ履歴：\u003C/b\u003E創薬には10〜15年の期間を要します。買収企業は、対象企業が広く認知される前に生成された臨床データへのアクセスを必要とする場合があります。このような膨大な履歴データを移行することは、通常時であっても大規模な作業であり、取引完了の期限が迫っている状況ではなおさらです。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E買収した研究ポートフォリオ内の休眠資産：\u003C/b\u003Eあらゆる製薬のR&D組織には、現在では当てはまらない理由で優先順位が下がったり、保留されたり、放棄されたりした化合物が何千も蓄積されています。スクリーニング結果、構造活性相関、吸収・分布・代謝・排泄（ADME）プロファイル、初期の毒性シグナル、作用機序研究などの休眠状態にある研究データは、長年投資されてきたR&D資本を意味します。しかし、これらは大規模に検索、コンテキスト化、分析できて初めて価値を持ちます。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E知的財産の来歴：\u003C/b\u003E特許ポートフォリオには数十億ドルの価値がありますが、その法的効力は基盤となる実験データの整合性に依存します。実験ノート、分析記録、合成ログは、検索可能で、帰属が明確であり、改ざんの痕跡が確認できる必要があります。データがレガシーシステムに分散していたり、管理の連鎖（チェーンオブカストディ）を示す文書なしに複数回移行されていたりする場合、これらの要件を満たすことは困難です。知的財産は、それを裏付けるデータと切り離すことはできません。特許請求の範囲の強さは、その背後にある実験的証拠の強さに依存します。このため、特許の出願と防御のサポート、大規模な実施の自由（FTO）分析、特許出願の継続性、営業秘密の保護において、M&A特有の課題が生じます。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E運用の継続性：\u003C/b\u003E統合の最中であっても、ビジネスが止まることはありません。営業担当者は引き続き医師を訪問します。製造部門は引き続き製品を生産します。これらの機能を支えるデータは、移行期間中も継続して利用可能であり、正確である必要があります。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Ch3\u003ESnowflakeによる課題の解決方法\u003C/h3\u003E\n\u003Ch4\u003E移行なしでの即時データアクセス\u003C/h4\u003E\n\u003Cp\u003E従来のM&Aにおける統合では、データを連携して使用する前に物理的に移動させる必要があると考えられており、これが最も業務に支障をきたすステップとなっています。Snowflakeのセキュアデータシェアリングアーキテクチャは、その要件を排除できます。\u003C/p\u003E\n\u003Cp\u003E取引完了の初日に、買収企業は対象企業のSnowflakeデータへの直接かつライブなアクセス権を付与されます。データの移動、抽出・変換・ロード（ETL）パイプライン、データの重複は一切発生しません。買収された企業のデータは、元の場所に留まります。親会社は、セキュアな共有を通じて、リアルタイムでデータに直接クエリを実行します。\u003C/p\u003E\n\u003Cp\u003Eライフサイエンス業界において、これは非常に重要です。臨床オペレーションチームは、買収された企業の治験ステータスデータを迅速に確認できます。財務部門は、統合レポート作成のために収益データを確認できます。薬事部門は、申請履歴にアクセスできます。移行タスクが1つ完了する前から、ビジネスは統合されたデータに基づいて稼働します。\u003C/p\u003E\n\u003Ch4\u003E規制環境向けのフェデレーテッドアーキテクチャ\u003C/h4\u003E\n\u003Cp\u003Eすべての買収で包括的なデータ統合が求められるわけではなく、ライフサイエンス業界では統合すべきでないことも多々あります。GxPコンプライアンス記録を持つ検証済みシステムは、そのまま維持し、システムレイヤーではなくレポートおよびアナリティクスレイヤーで統合を行う方が適していることがよくあります。\u003Cbr\u003E\n\u003C/p\u003E\n\u003Cp\u003ESnowflakeのマルチアカウントアーキテクチャは、まさにこのモデルをサポートしています。各事業体は、独自のSnowflakeアカウント（独自のアイデンティティ、独自のアクセス制御、独自の検証済み環境）を維持しながら、統合された可視性を得るために双方向でデータを共有します。親会社はすべての情報を確認できます。子会社は独立して業務を行います。検証状態は維持されます。\u003C/p\u003E\n\u003Ch4\u003E法的に機密性の高い統合期間向けのクリーンルーム\u003C/h4\u003E\n\u003Cp\u003Eライフサイエンス業界の買収では、両社が法的にすべてのデータを共有できない期間（数か月に及ぶこともあります）が頻繁に発生します。独占禁止法の審査期間、カーブアウトの制限、規制上の保留要件などはすべて、技術的な希望や制限の有無にかかわらず、法的に義務付けられたデータアクセスの制約を生み出します。\u003C/p\u003E\n\u003Cp\u003E\u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://docs.snowflake.com/en/user-guide/cleanrooms/about\"\u003ESnowflakeデータクリーンルーム\u003C/a\u003Eを使用すると、データへの共同アクセスなしで共同分析が可能になります。両当事者は、相手の基礎となる記録を見ることなく、セキュアなデータ分析を実行し、統合された予測を構築し、統合レポートを作成できます。計算は共有環境で行われ、生データが各当事者の制御下から離れることはありません。これは、規制当局の審査中である製品が関わる取引や、商業データが独占禁止法の審査対象となる場合に特に関連します。\u003C/p\u003E\n\u003Ch3\u003E事業売却：共に構築したものの分離\u003C/h3\u003E\n\u003Cp\u003E買収が複雑であるとすれば、事業売却はさらに困難です。データを追加するのではなく、切り離す作業だからです。\u003C/p\u003E\n\u003Cp\u003E製薬事業から診断部門をスピンオフする企業を想定します。これら2つの事業は共通のデータプラットフォームを共有しており、顧客、製造施設、臨床インフラストラクチャの共有など、長年にわたって混在した記録を持っている可能性があります。そのデータをきれいに分離し、取引のスケジュールとコストの制約内で実行することは、業界で最も困難なデータエンジニアリングの課題の1つです。\u003C/p\u003E\n\u003Cp\u003ESnowflakeは、いくつかの方法で事業売却の課題に対処します。\u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003Eゼロコピークローニング：\u003C/b\u003Eデータが実際に分岐するまでストレージコストを重複させることなく、特定の時点におけるデータベース、スキーマ、またはテーブルの独立したコピーを作成します。事業売却の発効日に、売却された事業体のデータドメインを新しいアカウントにクローンし、新しいスタンドアロン企業にクリーンな出発点を提供できます。元のデータは、親アカウント内で手付かずのまま残ります。正式な分離プロセスがバックグラウンドで継続する間、両社はそれぞれのコピーで業務を行います\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E行および列レベルのセキュリティ：\u003C/b\u003E移行期間中に、ピンポイントでのデータ制限を可能にします。完全な分離が実行されている間、データモデル全体を再構築することなく、分離契約の下でアクセス権を持つデータのみを表示するように、売却された事業体のユーザーを特定の行と列に至るまで制限できます\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003Eオブジェクトのタグ付けとデータ分類：\u003C/b\u003E分離が発表される前に、どのデータ資産がどのビジネスユニットに属しているかを企業がインベントリ化できるようにします。どのようなデータが存在し、どこにあり、誰がそれに依存しているかを把握するこの作業には、通常、数か月の手作業が必要です。Snowflakeのタグ付けとリネージ機能により、この作業を大幅に短縮できます\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003ETime Travelと不変の監査証跡：\u003C/b\u003E特許の優先権証明書類をサポートできる、再構築可能なデータ履歴を作成します。保持期間内の任意の時点におけるすべてのデータ状態を再構築できます。Snowflake \u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://www.snowflake.com/en/blog/regulated-workloads-snowflake-backups/\"\u003EBackups\u003C/a\u003Eを使用すると、長期的なデータ保持要件をサポートするように設計された不変の形式で、重要なデータをSnowflakeに最大10年間保持できます\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003Eクロスアカウントのデータ共有：\u003C/b\u003E社内外を問わず、特許弁護士が検証済みシステムから移行することなく、裏付けデータにアクセスできるようにします\u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://www.snowflake.com/en/product/features/cortex/\"\u003ESnowflake Cortex\u003C/a\u003EのAI機能により、特許状況や社内の研究記録の大規模な分析が可能になり、FTO（実施の自由）のギャップなどのリスクと、取得したデータに含まれる未出願の特許対象などの機会の両方を特定できます。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003Eガバナンスとアクセス制御：\u003C/b\u003E統合期間中に営業秘密が意図せず開示されるのを防ぐのに役立ちます。これは、法的な統合が完了する前に両組織の従業員が共同作業を開始する場合に特に重要です。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Ch3\u003E実際のライフサイエンスのパターン：スピンオフ企業\u003C/h3\u003E\n\u003Cp\u003Eライフサイエンス分野で頻繁に見られるパターンの1つが、大規模なスピンオフです。これは、親会社が一部の事業部門を売却し、新たな独立した事業体を設立するケースです。このような取引は完了の数か月から数年前に発表され、新しい事業体は初日から運用面で独立していることが求められます。\u003C/p\u003E\n\u003Cp\u003Eここでのデータの課題は重大です。新しい事業体は、独自のデータプラットフォーム、独自のガバナンスモデル、および長年の履歴データへのアクセスを必要としますが、親会社からすべてをそのまま引き継ぐことはできません。一方で親会社は、中断することなく同じデータで運用を続ける必要があります。\u003C/p\u003E\n\u003Cp\u003ESnowflakeのアーキテクチャは、アカウントレプリケーション、選択的なデータ共有、クローニングの組み合わせにより、この課題に対処するように設計されています。新しい事業体は独自のアカウントを取得し、権限を持つデータのクローン化されたコピーを受け取り、移行期間中はライブ共有を通じて親会社からの共有データにアクセスできます。親会社は通常通り運用を継続します。新しい事業体は、共有インフラストラクチャへのアクセスを維持しながら、独立したプラットフォームを構築します。さらに、Snowflakeのオブジェクトのタグ付け、行レベルセキュリティ、アクセスロギングの組み合わせにより、どのデータがどの事業体に割り当てられたか、いつアクセスが付与または取り消されたか、分離時のデータの状態はどうであったかを示す監査可能な記録が作成されます。この監査証跡は、分離プロセスのドキュメント要件をサポートすることと、将来のIP（知的財産）に関する疑問に関連する再構築可能なデータ記録を提供することの、2つの目的を果たします。\u003C/p\u003E\n\u003Cp\u003E何か月もかかるはずだった移行作業のプロセスが、大幅に短い期間でビジネス価値を生み出し始めることができます。\u003C/p\u003E\n\u003Ch3\u003E取引価値を加速させる分析機能\u003C/h3\u003E\n\u003Cp\u003E従来のM&A統合の定石では、データ統合が分析の前提条件として扱われます。まずデータを移動し、次にレポートを作成し、その後にインサイトを生成します。この順次的なアプローチでは、買収企業は取引完了から数か月経つまで、実際に何を購入したのかを詳細なデータドリブンのレベルで理解できないことがよくあります。Snowflakeは、このシーケンスを逆転させます。セキュアデータシェアリングを通じてデータをその場でクエリできるため、分析ワークロードを迅速に開始でき、以下の機能を実現できます。\u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E統合にまで及ぶデューデリジェンス：\u003C/b\u003E収益予測、パイプラインの確率評価、製造コスト分析など、デューデリジェンス中に構築された分析モデルは、取引完了後に運用ダッシュボードへ直接移行できます。これらは、取引プロセスで使用される静的なスナップショットではなく、ライブデータに対して実行されます。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003ER&Dポートフォリオの最適化：\u003C/b\u003E両社の研究プログラム全体にわたる統合された可視性により、データサイエンスチームは、冗長性（同じメカニズムを追求する2つのプログラム）、相乗効果（一方の企業の遺伝学データによって検証され、もう一方の企業の化学技術によって創薬可能なターゲット）、およびホワイトスペースの機会を迅速に特定できます。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E統合データセットでのコマーシャルアナリティクス：\u003C/b\u003E両事業体の処方箋データ、支払者データ、およびリアルワールドエビデンスを一緒に分析することで、CRMやデータウェアハウスの統合を待たずに、クロスセルの機会、カバレッジのギャップ、および競争上のポジショニングを特定できます。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E統合ポートフォリオ全体での安全性シグナルの検出：\u003C/b\u003Eファーマコビジランス（医薬品安全性監視）チームは、統合された製品ポートフォリオ全体にわたる有害事象データを迅速にクエリし、どちらの企業も単独では検出できなかった潜在的なクラスエフェクトや薬物相互作用を特定できます。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003Eレギュラトリーインテリジェンス：\u003C/b\u003E両社の規制当局への申請履歴、FDAの会議議事録、および通信記録を関連付けることで、統合ポートフォリオに影響を与える前例、コミットメント、およびリスクを特定するのに役立ちます。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cp\u003Eこれらは将来の機能ではありません。Snowflakeを利用している組織であれば、初日から実現可能です。これは、従来の分析作業の障壁となっていた移行という前提条件を、このアーキテクチャが排除するためです。\u003C/p\u003E\n\u003Ch3\u003E競争優位性をもたらす時間\u003C/h3\u003E\n\u003Cp\u003EライフサイエンスのM&Aにおいて、スピードは通常の取引の根拠を超える理由で重要になります。商業業務における相乗効果は、統合された顧客データに依存します。R&Dの生産性は、研究チームが自社のパイプラインと並行して、取得したパイプラインを確認できるかどうかに依存します。製造に関する意思決定は、両事業体にまたがるサプライチェーンの可視性に依存します。統合が1か月遅れるごとに、1か月分の相乗効果の価値が失われます。事業売却が1か月長引くごとに、両者にコストをもたらす運用上の複雑さが1か月分増すことになります。取引において統合のスピードが競合差別化要因となる中、この業界でM&Aを効果的に実行したい企業は、データプラットフォームを単なるITプロジェクトではなく、取引実行の資産として扱う必要があります。Snowflakeのアーキテクチャは、統合や移行ではなく、管理されたコラボレーション、フェデレーション、ガバナンスを中心に構築されており、ライフサイエンスの取引が実際に機能すべき方法と自然に一致しています。\u003C/p\u003E\n\u003Cp\u003E取引が完了すると、データの作業が始まります。適切なプラットフォームがあれば、以前ほど時間はかかりません。\u003C/p\u003E\n\u003Cp\u003E\u003Cb\u003E\u003Ci\u003ESnowflakeによるライフサイエンスのM&Aおよび事業売却シナリオのサポートについて、詳しくは\u003Ca href=\"https://www.snowflake.com/en/contact/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Eお問い合わせください。\u003C/a\u003E\u003C/i\u003E\u003C/b\u003E\u003C/p\u003E\n\u003Cp\u003E\u003Cb\u003E\u003Ci\u003Eライフサイエンス組織をサポートするSnowflakeの最新機能について、詳しくは\u003Ca href=\"https://www.snowflake.com/webinars/snowflake-summit-encore-life-sciences-20260819/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESummit Encore for Life Sciences\u003C/a\u003Eをご視聴ください。\u003C/i\u003E\u003C/b\u003E\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"}},":itemsOrder":["blog_text"],":type":"wcm/foundation/components/responsivegrid"},"responsivegrid_premium_content_banner":{"columnCount":12,"columnClassNames":{},"gridClassNames":"aem-Grid aem-Grid--12 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Atnoor","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--bb147556-ba05-4306-bad7-23f32cf2a52c/deven-atnoor-bio.jpg?quality=85&preferwebp=true","lazyEnabled":true,"isLcpImage":false,"width":"1024",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-efbb4ede2d","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/deven-atnoor/"},"linkTargetContentType":"DOCUMENT_LEARN",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Deven Atnoor"},"authorTitle":"Life Sciences Field CTO"},{"authorImage":{"id":"image-303dffa389","height":"926","alt":" Olga Teplitsky","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--825d58f2-5c25-4800-b806-98de47de87a8/olga-t.jpg?quality=85&preferwebp=true","lazyEnabled":true,"isLcpImage":false,"width":"936",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-7c2f9a6fec","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/olga-teplitsky/"},"linkTargetContentType":"DOCUMENT_LEARN",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Olga Teplitsky"},"authorTitle":"Sr. District Manager, Majors"}],":type":"snowflake-site/components/blog/author-chip"}},":itemsOrder":["author_chip"],"appliedCssClassNames":"snowflake-responsive-component-top-padding-medium",":type":"snowflake-site/components/container"},"container_share_article":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"share_article":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 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